Activity grouping (except CNAE 56, 64-66 and 95.1);Main variables;Size of the enterprise;Total
Total Enterprises;F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;8,47
Total Enterprises;F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;6,84
Total Enterprises;F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;13,83
Total Enterprises;F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;28,53
Total Enterprises;F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;6,31
Total Enterprises;F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;4,89
Total Enterprises;F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;10,95
Total Enterprises;F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;23,83
Total Enterprises;F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;39,45
Total Enterprises;F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;31,06
Total Enterprises;F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;50,27
Total Enterprises;F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;64,17
Total Enterprises;F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;52,99
Total Enterprises;F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;54,53
Total Enterprises;F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;49,67
Total Enterprises;F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;51,57
Total Enterprises;F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;44,29
Total Enterprises;F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;43,33
Total Enterprises;F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;44,86
Total Enterprises;F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;48,67
Total Enterprises;F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;34,27
Total Enterprises;F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;30,85
Total Enterprises;F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;37,28
Total Enterprises;F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;47,67
Total Enterprises;F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;58,66
Total Enterprises;F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;53,43
Total Enterprises;F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;66,2
Total Enterprises;F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;72,18
Total Enterprises;F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;19,47
Total Enterprises;F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;19,47
Total Enterprises;F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;16,1
Total Enterprises;F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;27,51
Total Enterprises;F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;38,84
Total Enterprises;F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;42,41
Total Enterprises;F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;33,15
Total Enterprises;F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;30,92
Total Enterprises;F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;3,62
Total Enterprises;F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;2,89
Total Enterprises;F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;5,84
Total Enterprises;F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;13,42
Total Enterprises;F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;5,91
Total Enterprises;F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;4,88
Total Enterprises;F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;10,23
Total Enterprises;F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;18,47
Total Enterprises;F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;41,34
Total Enterprises;F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;45,33
Total Enterprises;F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;33,67
Total Enterprises;F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;27,63
Total Enterprises;F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;60,11
Total Enterprises;F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;62,42
Total Enterprises;F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;55,19
Total Enterprises;F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;53,81
Total Enterprises;F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;46,4
Total Enterprises;F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;46,85
Total Enterprises;F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;46,1
Total Enterprises;F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;42,97
Total Enterprises;F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;48,76
Total Enterprises;F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;50,94
Total Enterprises;F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;47,25
Total Enterprises;F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;31,95
Total Enterprises;F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;23,64
Total Enterprises;F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;27,12
Total Enterprises;F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;16,42
Total Enterprises;F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;13,51
Total Enterprises;F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;57,61
Total Enterprises;F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;57,72
Total Enterprises;F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;57,8
Total Enterprises;F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;55,92
Total Enterprises;F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;34,8
Total Enterprises;F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;36,23
Total Enterprises;F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;31,9
Total Enterprises;F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;30,37
Total Enterprises;F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;17,23
Total Enterprises;F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;18,45
Total Enterprises;F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;15,19
Total Enterprises;F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;11,94
Total Enterprises;F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;32,04
Total Enterprises;F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;34,76
Total Enterprises;F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;25,02
Total Enterprises;F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;28,97
Total Enterprises;F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;8,47
Total Enterprises;F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;6,52
Total Enterprises;F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;12,28
Total Enterprises;F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;12,63
Total Enterprises;F.7 % of enterprises that purchased or accessed Big Data (4);Total;10,26
Total Enterprises;F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;8,78
Total Enterprises;F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;11,3
Total Enterprises;F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;18,03
Total Enterprises;F.8 % enterprises with specific training in Big Data (4);Total;12,12
Total Enterprises;F.8 % enterprises with specific training in Big Data (4);From 10 to 49;10,49
Total Enterprises;F.8 % enterprises with specific training in Big Data (4);From 50 to 249;12,43
Total Enterprises;F.8 % enterprises with specific training in Big Data (4);250 or more;22,81
Total Enterprises;F.9 % enterprises with Big Data training provided by external providers (5);Total;87,45
Total Enterprises;F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;85,79
Total Enterprises;F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;91,01
Total Enterprises;F.9 % enterprises with Big Data training provided by external providers (5);250 or more;87,95
1. Total Industry (CNAE 10-39);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;6,43
1. Total Industry (CNAE 10-39);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;4,53
1. Total Industry (CNAE 10-39);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;11,32
1. Total Industry (CNAE 10-39);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;28,23
1. Total Industry (CNAE 10-39);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;4,51
1. Total Industry (CNAE 10-39);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;2,79
1. Total Industry (CNAE 10-39);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;8,83
1. Total Industry (CNAE 10-39);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;24,72
1. Total Industry (CNAE 10-39);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;55,08
1. Total Industry (CNAE 10-39);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;32,66
1. Total Industry (CNAE 10-39);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;70,65
1. Total Industry (CNAE 10-39);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;88,85
1. Total Industry (CNAE 10-39);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;49,16
1. Total Industry (CNAE 10-39);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;56,85
1. Total Industry (CNAE 10-39);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;40,86
1. Total Industry (CNAE 10-39);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;42,75
1. Total Industry (CNAE 10-39);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;36,77
1. Total Industry (CNAE 10-39);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;40,63
1. Total Industry (CNAE 10-39);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;32,99
1. Total Industry (CNAE 10-39);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;32,9
1. Total Industry (CNAE 10-39);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;28,16
1. Total Industry (CNAE 10-39);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;22,58
1. Total Industry (CNAE 10-39);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;27,79
1. Total Industry (CNAE 10-39);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;44,04
1. Total Industry (CNAE 10-39);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;48,54
1. Total Industry (CNAE 10-39);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;38,37
1. Total Industry (CNAE 10-39);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;52,47
1. Total Industry (CNAE 10-39);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;69,36
1. Total Industry (CNAE 10-39);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;21,76
1. Total Industry (CNAE 10-39);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;30,2
1. Total Industry (CNAE 10-39);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;8,92
1. Total Industry (CNAE 10-39);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;21,3
1. Total Industry (CNAE 10-39);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;40,04
1. Total Industry (CNAE 10-39);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;37,84
1. Total Industry (CNAE 10-39);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;47,81
1. Total Industry (CNAE 10-39);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;32,43
1. Total Industry (CNAE 10-39);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;3,21
1. Total Industry (CNAE 10-39);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;2,46
1. Total Industry (CNAE 10-39);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;4,92
1. Total Industry (CNAE 10-39);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;13,05
1. Total Industry (CNAE 10-39);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;4,47
1. Total Industry (CNAE 10-39);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;2,69
1. Total Industry (CNAE 10-39);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;11,17
1. Total Industry (CNAE 10-39);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;20,85
1. Total Industry (CNAE 10-39);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;38,45
1. Total Industry (CNAE 10-39);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;48,72
1. Total Industry (CNAE 10-39);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;28,26
1. Total Industry (CNAE 10-39);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;29,14
1. Total Industry (CNAE 10-39);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;50,09
1. Total Industry (CNAE 10-39);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;44,04
1. Total Industry (CNAE 10-39);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;56,72
1. Total Industry (CNAE 10-39);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;53,55
1. Total Industry (CNAE 10-39);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;50,02
1. Total Industry (CNAE 10-39);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;47,02
1. Total Industry (CNAE 10-39);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;51,95
1. Total Industry (CNAE 10-39);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;56,12
1. Total Industry (CNAE 10-39);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;54,41
1. Total Industry (CNAE 10-39);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;64,86
1. Total Industry (CNAE 10-39);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;45,82
1. Total Industry (CNAE 10-39);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;39,16
1. Total Industry (CNAE 10-39);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;24,25
1. Total Industry (CNAE 10-39);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;33,19
1. Total Industry (CNAE 10-39);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;16,86
1. Total Industry (CNAE 10-39);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;11,28
1. Total Industry (CNAE 10-39);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;66,32
1. Total Industry (CNAE 10-39);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;73,51
1. Total Industry (CNAE 10-39);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;60,41
1. Total Industry (CNAE 10-39);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;55,81
1. Total Industry (CNAE 10-39);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;36,02
1. Total Industry (CNAE 10-39);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;39,69
1. Total Industry (CNAE 10-39);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;30,98
1. Total Industry (CNAE 10-39);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;37,25
1. Total Industry (CNAE 10-39);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;21,09
1. Total Industry (CNAE 10-39);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;31,77
1. Total Industry (CNAE 10-39);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;10,53
1. Total Industry (CNAE 10-39);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;11,22
1. Total Industry (CNAE 10-39);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;34,32
1. Total Industry (CNAE 10-39);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;44,08
1. Total Industry (CNAE 10-39);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;23,14
1. Total Industry (CNAE 10-39);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;30,26
1. Total Industry (CNAE 10-39);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;4
1. Total Industry (CNAE 10-39);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;1,12
1. Total Industry (CNAE 10-39);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;6,65
1. Total Industry (CNAE 10-39);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;9,96
1. Total Industry (CNAE 10-39);F.7 % of enterprises that purchased or accessed Big Data (4);Total;6,92
1. Total Industry (CNAE 10-39);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;3,4
1. Total Industry (CNAE 10-39);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;8,39
1. Total Industry (CNAE 10-39);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;17,7
1. Total Industry (CNAE 10-39);F.8 % enterprises with specific training in Big Data (4);Total;7,84
1. Total Industry (CNAE 10-39);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;1,85
1. Total Industry (CNAE 10-39);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;13
1. Total Industry (CNAE 10-39);F.8 % enterprises with specific training in Big Data (4);250 or more;20,84
1. Total Industry (CNAE 10-39);F.9 % enterprises with Big Data training provided by external providers (5);Total;93,11
1. Total Industry (CNAE 10-39);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;100
1. Total Industry (CNAE 10-39);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;98,53
1. Total Industry (CNAE 10-39);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;84,08
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;4,79
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;3,44
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;10,27
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;18,79
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;3,02
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;1,84
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;7,49
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;16,78
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;59,03
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;49,95
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;60,01
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;88,73
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;45,37
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;60,68
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;21,74
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;47,76
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;49,01
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;59,32
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;34,2
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;48
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;24,61
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;17,84
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;27,55
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;41,44
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;46,77
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;41,05
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;39,1
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;85,25
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;10,31
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;8,9
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;7,55
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;21,87
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;50,05
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;50,05
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;63,68
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;17,5
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;2,52
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;1,76
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;5,95
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;8,56
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;2,96
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;1,83
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;7,86
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;17,33
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;49,46
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;61,67
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;37,87
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;31,38
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;42,47
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;29,39
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;58,3
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;52,69
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;49,31
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;49,35
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;49,57
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;48,44
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;46,09
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;55,11
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;38,24
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;30,83
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;24,09
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;38,12
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;6,35
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;15,2
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;66,58
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;73,77
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;53,61
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;72,37
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;34,6
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;49,35
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;10,05
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;41
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;25,8
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;42,73
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;2,33
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;20,55
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;47,46
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;66,34
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;26,38
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;27,93
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;2,67
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;0
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;4,91
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;11,86
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.7 % of enterprises that purchased or accessed Big Data (4);Total;5,05
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;0
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;8,97
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;23,33
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.8 % enterprises with specific training in Big Data (4);Total;4,82
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;0
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;7,21
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.8 % enterprises with specific training in Big Data (4);250 or more;26,2
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.9 % enterprises with Big Data training provided by external providers (5);Total;76,34
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;.
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;100
1.1. Food, beverages, tobacco, textile, clothing, leather and footwear, wood and cork, paper, graphic arts and reproduction of recorded media (CNAE 10-18);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;57,31
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;9,17
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;6,98
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;11,82
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;30,98
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;6,71
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;4,92
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;8,88
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;24,49
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;39,75
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;12,35
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;64,99
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;83,6
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;63,02
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;83,14
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;48,98
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;23,65
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;29,29
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;30,11
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;26,08
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;31,93
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;26,84
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;11,62
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;42,14
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;49,13
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;35
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;19,29
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;48,47
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;61,76
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;32,21
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;50,6
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;4,39
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;20,21
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;41,04
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;37,22
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;49,33
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;39,51
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;3,78
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;2,45
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;5,9
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;14,74
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;8,08
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;4,92
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;15,91
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;29,21
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;40,76
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;59,82
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;20,06
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;38,1
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;57,07
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;58,66
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;52,49
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;65,59
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;57,31
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;55,79
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;56,31
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;65,64
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;57,55
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;66,7
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;53,31
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;38,81
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;19,15
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;19,35
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;21,21
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;12,11
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;55,28
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;56,55
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;55,72
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;49,54
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;24,42
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;8,6
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;37,85
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;38,12
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;16
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;8,6
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;27,48
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;6,41
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;13,29
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;11,48
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;8,69
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;33,71
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;3,37
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;0
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;7,94
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;7,3
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.7 % of enterprises that purchased or accessed Big Data (4);Total;7,4
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;0
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;12,07
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;25,09
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.8 % enterprises with specific training in Big Data (4);Total;14,04
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;8,7
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;23,84
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.8 % enterprises with specific training in Big Data (4);250 or more;15,95
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.9 % enterprises with Big Data training provided by external providers (5);Total;98,39
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;100
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;100
1.2 Coke and petroleum refining pharmaceutical products rubber and plastics non-metallic mineral products (CNAE 19-23);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;91,28
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;6,04
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;5,37
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;7,92
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;23,52
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;4,6
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;3,97
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;6,82
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;18,11
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;29,51
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;13
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;69,71
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;88,47
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;52,13
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;52,07
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;56,4
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;41,11
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;44,23
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;45,77
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;52,76
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;5,32
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;23,14
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;22,65
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;17,74
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;42,73
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;30,55
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;22,33
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;49,69
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;62,26
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;25,9
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;33,08
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;6,51
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;5,32
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;43,94
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;44,58
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;43,8
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;37,74
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;3,4
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;3,51
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;1,68
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;10,61
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;3,46
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;2,01
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;11
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;21,73
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;11,04
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;0
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;23,99
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;12,92
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;26,71
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;8,23
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;42,11
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;57,43
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;23,89
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;8,23
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;37,28
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;48,38
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;71
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;100
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;44,88
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;31,47
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;9,9
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;0
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;22,67
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;6,46
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;75,69
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;91,77
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;60,7
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;55,98
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;68,9
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;100
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;38,4
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;37,42
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;50,07
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;91,77
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;10,97
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;0
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;16,54
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;8,23
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;23,35
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;30,82
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;3,61
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;2,73
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;5,43
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;8,65
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.7 % of enterprises that purchased or accessed Big Data (4);Total;3,19
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;2,73
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;6,5
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;0
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.8 % enterprises with specific training in Big Data (4);Total;2,46
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;0
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;7,3
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.8 % enterprises with specific training in Big Data (4);250 or more;16,85
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.9 % enterprises with Big Data training provided by external providers (5);Total;100
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;.
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;100
1.3 Metallurgy, manufacture of metallic products (CNAE 24-25);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;100
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;5,94
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;3,29
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;11,51
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;31,91
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;4,11
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;1,61
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;9,36
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;28,75
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;68,98
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;41,57
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;75,91
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;88,7
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;32,42
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;21,48
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;38,31
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;35,45
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;27,79
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;29,94
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;31,47
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;19,71
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;34,63
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;60,6
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;18,7
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;30,45
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;71,98
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;89,13
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;64,06
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;65,19
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;24,47
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;47,4
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;14,02
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;15,17
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;26,1
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;0
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;37,05
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;38,13
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;2,94
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;2,18
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;4,34
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;11,4
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;5,45
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;3,48
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;12,56
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;17,05
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;45,33
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;58,25
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;33,08
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;26,83
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;65,02
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;67,63
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;67,78
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;37,45
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;57,94
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;59,06
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;55,98
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;60,41
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;56,4
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;64,08
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;49,55
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;43,45
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;39,15
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;61,45
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;16,72
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;12,96
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;70,72
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;76,86
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;67,36
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;50,68
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;32,15
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;29,4
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;35,46
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;32,91
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;10,66
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;17,48
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;1,53
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;13
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;51,02
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;67,71
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;33,88
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;33,01
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;6,97
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;3,19
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;11,38
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;7,12
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.7 % of enterprises that purchased or accessed Big Data (4);Total;11,45
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;14,64
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;9,16
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;8,86
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.8 % enterprises with specific training in Big Data (4);Total;9,97
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;0
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;17,35
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.8 % enterprises with specific training in Big Data (4);250 or more;17,72
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.9 % enterprises with Big Data training provided by external providers (5);Total;92,3
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;.
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;95,87
1.4. Computer, electronic and optical products electric equipment, machinery and mechanical equipment motor vehicles transport material furniture manufacturing industry, repair of machinery and equipment (CNAE 26-33);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;86,31
1.5. Energy and water (CNAE 35-39);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;13,73
1.5. Energy and water (CNAE 35-39);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;8,87
1.5. Energy and water (CNAE 35-39);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;20,91
1.5. Energy and water (CNAE 35-39);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;43,39
1.5. Energy and water (CNAE 35-39);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;10,29
1.5. Energy and water (CNAE 35-39);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;5,38
1.5. Energy and water (CNAE 35-39);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;16,84
1.5. Energy and water (CNAE 35-39);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;42,35
1.5. Energy and water (CNAE 35-39);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;87,47
1.5. Energy and water (CNAE 35-39);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;78,97
1.5. Energy and water (CNAE 35-39);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;90,53
1.5. Energy and water (CNAE 35-39);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;95,22
1.5. Energy and water (CNAE 35-39);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;55,89
1.5. Energy and water (CNAE 35-39);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;40,26
1.5. Energy and water (CNAE 35-39);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;60,68
1.5. Energy and water (CNAE 35-39);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;71,19
1.5. Energy and water (CNAE 35-39);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;29,25
1.5. Energy and water (CNAE 35-39);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;15,86
1.5. Energy and water (CNAE 35-39);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;27,51
1.5. Energy and water (CNAE 35-39);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;49,58
1.5. Energy and water (CNAE 35-39);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;34,2
1.5. Energy and water (CNAE 35-39);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;12,5
1.5. Energy and water (CNAE 35-39);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;34,2
1.5. Energy and water (CNAE 35-39);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;63,67
1.5. Energy and water (CNAE 35-39);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;62,86
1.5. Energy and water (CNAE 35-39);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;56,1
1.5. Energy and water (CNAE 35-39);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;64,17
1.5. Energy and water (CNAE 35-39);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;70,41
1.5. Energy and water (CNAE 35-39);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;16,33
1.5. Energy and water (CNAE 35-39);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;6,49
1.5. Energy and water (CNAE 35-39);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;9,82
1.5. Energy and water (CNAE 35-39);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;37,76
1.5. Energy and water (CNAE 35-39);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;35,43
1.5. Energy and water (CNAE 35-39);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;37,41
1.5. Energy and water (CNAE 35-39);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;38,37
1.5. Energy and water (CNAE 35-39);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;29,1
1.5. Energy and water (CNAE 35-39);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;7,05
1.5. Energy and water (CNAE 35-39);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;5,36
1.5. Energy and water (CNAE 35-39);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;6,19
1.5. Energy and water (CNAE 35-39);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;27,79
1.5. Energy and water (CNAE 35-39);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;4,81
1.5. Energy and water (CNAE 35-39);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;2,66
1.5. Energy and water (CNAE 35-39);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;8,72
1.5. Energy and water (CNAE 35-39);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;24,61
1.5. Energy and water (CNAE 35-39);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;8,9
1.5. Energy and water (CNAE 35-39);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;0
1.5. Energy and water (CNAE 35-39);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;12,85
1.5. Energy and water (CNAE 35-39);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;19,35
1.5. Energy and water (CNAE 35-39);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;34,9
1.5. Energy and water (CNAE 35-39);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;13,6
1.5. Energy and water (CNAE 35-39);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;50,54
1.5. Energy and water (CNAE 35-39);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;50,39
1.5. Energy and water (CNAE 35-39);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;43,4
1.5. Energy and water (CNAE 35-39);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;27,68
1.5. Energy and water (CNAE 35-39);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;58,24
1.5. Energy and water (CNAE 35-39);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;49,73
1.5. Energy and water (CNAE 35-39);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;27,02
1.5. Energy and water (CNAE 35-39);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;13,6
1.5. Energy and water (CNAE 35-39);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;20,56
1.5. Energy and water (CNAE 35-39);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;61,97
1.5. Energy and water (CNAE 35-39);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;9,01
1.5. Energy and water (CNAE 35-39);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;0
1.5. Energy and water (CNAE 35-39);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;25,7
1.5. Energy and water (CNAE 35-39);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;0
1.5. Energy and water (CNAE 35-39);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;71,88
1.5. Energy and water (CNAE 35-39);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;85,92
1.5. Energy and water (CNAE 35-39);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;76,45
1.5. Energy and water (CNAE 35-39);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;38,7
1.5. Energy and water (CNAE 35-39);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;35,65
1.5. Energy and water (CNAE 35-39);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;31
1.5. Energy and water (CNAE 35-39);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;42,83
1.5. Energy and water (CNAE 35-39);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;33,24
1.5. Energy and water (CNAE 35-39);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;3,94
1.5. Energy and water (CNAE 35-39);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;0
1.5. Energy and water (CNAE 35-39);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;6,42
1.5. Energy and water (CNAE 35-39);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;7,44
1.5. Energy and water (CNAE 35-39);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;31,79
1.5. Energy and water (CNAE 35-39);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;43,8
1.5. Energy and water (CNAE 35-39);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;24,41
1.5. Energy and water (CNAE 35-39);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;20,84
1.5. Energy and water (CNAE 35-39);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;3,63
1.5. Energy and water (CNAE 35-39);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;0
1.5. Energy and water (CNAE 35-39);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;0
1.5. Energy and water (CNAE 35-39);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;17
1.5. Energy and water (CNAE 35-39);F.7 % of enterprises that purchased or accessed Big Data (4);Total;7,74
1.5. Energy and water (CNAE 35-39);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;4,38
1.5. Energy and water (CNAE 35-39);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;1,27
1.5. Energy and water (CNAE 35-39);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;24,82
1.5. Energy and water (CNAE 35-39);F.8 % enterprises with specific training in Big Data (4);Total;7,69
1.5. Energy and water (CNAE 35-39);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;0
1.5. Energy and water (CNAE 35-39);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;4,87
1.5. Energy and water (CNAE 35-39);F.8 % enterprises with specific training in Big Data (4);250 or more;28,73
1.5. Energy and water (CNAE 35-39);F.9 % enterprises with Big Data training provided by external providers (5);Total;100
1.5. Energy and water (CNAE 35-39);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;.
1.5. Energy and water (CNAE 35-39);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;100
1.5. Energy and water (CNAE 35-39);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;100
2. Total Construction (CNAE 41-43);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;4,33
2. Total Construction (CNAE 41-43);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;3,94
2. Total Construction (CNAE 41-43);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;6,87
2. Total Construction (CNAE 41-43);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;19,02
2. Total Construction (CNAE 41-43);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;3,09
2. Total Construction (CNAE 41-43);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;2,68
2. Total Construction (CNAE 41-43);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;5,96
2. Total Construction (CNAE 41-43);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;16,3
2. Total Construction (CNAE 41-43);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;48,23
2. Total Construction (CNAE 41-43);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;45,93
2. Total Construction (CNAE 41-43);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;51,29
2. Total Construction (CNAE 41-43);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;79,84
2. Total Construction (CNAE 41-43);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;62,02
2. Total Construction (CNAE 41-43);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;63,21
2. Total Construction (CNAE 41-43);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;54,32
2. Total Construction (CNAE 41-43);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;73,76
2. Total Construction (CNAE 41-43);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;44,43
2. Total Construction (CNAE 41-43);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;44,85
2. Total Construction (CNAE 41-43);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;40,52
2. Total Construction (CNAE 41-43);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;54,01
2. Total Construction (CNAE 41-43);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;20,2
2. Total Construction (CNAE 41-43);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;14,62
2. Total Construction (CNAE 41-43);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;39,07
2. Total Construction (CNAE 41-43);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;44,76
2. Total Construction (CNAE 41-43);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;44,58
2. Total Construction (CNAE 41-43);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;45,18
2. Total Construction (CNAE 41-43);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;37,51
2. Total Construction (CNAE 41-43);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;64,92
2. Total Construction (CNAE 41-43);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;25,65
2. Total Construction (CNAE 41-43);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;23,06
2. Total Construction (CNAE 41-43);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;35,21
2. Total Construction (CNAE 41-43);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;33,43
2. Total Construction (CNAE 41-43);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;47,87
2. Total Construction (CNAE 41-43);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;50,21
2. Total Construction (CNAE 41-43);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;42,42
2. Total Construction (CNAE 41-43);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;26,24
2. Total Construction (CNAE 41-43);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;1,62
2. Total Construction (CNAE 41-43);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;1,41
2. Total Construction (CNAE 41-43);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;3,3
2. Total Construction (CNAE 41-43);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;5,93
2. Total Construction (CNAE 41-43);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;2,75
2. Total Construction (CNAE 41-43);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;2,5
2. Total Construction (CNAE 41-43);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;4,66
2. Total Construction (CNAE 41-43);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;10,97
2. Total Construction (CNAE 41-43);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;56,21
2. Total Construction (CNAE 41-43);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;62,83
2. Total Construction (CNAE 41-43);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;25,46
2. Total Construction (CNAE 41-43);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;28,12
2. Total Construction (CNAE 41-43);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;64,2
2. Total Construction (CNAE 41-43);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;64,18
2. Total Construction (CNAE 41-43);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;68,99
2. Total Construction (CNAE 41-43);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;35,56
2. Total Construction (CNAE 41-43);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;34,67
2. Total Construction (CNAE 41-43);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;35,39
2. Total Construction (CNAE 41-43);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;30,8
2. Total Construction (CNAE 41-43);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;34,8
2. Total Construction (CNAE 41-43);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;41,69
2. Total Construction (CNAE 41-43);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;37,21
2. Total Construction (CNAE 41-43);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;67,69
2. Total Construction (CNAE 41-43);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;28,88
2. Total Construction (CNAE 41-43);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;9,61
2. Total Construction (CNAE 41-43);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;8,33
2. Total Construction (CNAE 41-43);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;18,03
2. Total Construction (CNAE 41-43);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;0
2. Total Construction (CNAE 41-43);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;44,28
2. Total Construction (CNAE 41-43);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;37,57
2. Total Construction (CNAE 41-43);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;78,5
2. Total Construction (CNAE 41-43);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;54,15
2. Total Construction (CNAE 41-43);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;38,5
2. Total Construction (CNAE 41-43);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;38,28
2. Total Construction (CNAE 41-43);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;36,74
2. Total Construction (CNAE 41-43);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;56,44
2. Total Construction (CNAE 41-43);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;5,27
2. Total Construction (CNAE 41-43);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;4,28
2. Total Construction (CNAE 41-43);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;11,45
2. Total Construction (CNAE 41-43);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;0
2. Total Construction (CNAE 41-43);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;37,86
2. Total Construction (CNAE 41-43);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;44,6
2. Total Construction (CNAE 41-43);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;5,16
2. Total Construction (CNAE 41-43);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;17,73
2. Total Construction (CNAE 41-43);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;5,47
2. Total Construction (CNAE 41-43);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;3,76
2. Total Construction (CNAE 41-43);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;16,2
2. Total Construction (CNAE 41-43);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;0
2. Total Construction (CNAE 41-43);F.7 % of enterprises that purchased or accessed Big Data (4);Total;0,45
2. Total Construction (CNAE 41-43);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;0
2. Total Construction (CNAE 41-43);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;2,1
2. Total Construction (CNAE 41-43);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;4,14
2. Total Construction (CNAE 41-43);F.8 % enterprises with specific training in Big Data (4);Total;3,23
2. Total Construction (CNAE 41-43);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;3,41
2. Total Construction (CNAE 41-43);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;0
2. Total Construction (CNAE 41-43);F.8 % enterprises with specific training in Big Data (4);250 or more;13,14
2. Total Construction (CNAE 41-43);F.9 % enterprises with Big Data training provided by external providers (5);Total;100
2. Total Construction (CNAE 41-43);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;100
2. Total Construction (CNAE 41-43);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;.
2. Total Construction (CNAE 41-43);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;100
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;10,39
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;8,61
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;16,06
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;29,24
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;7,89
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;6,39
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;12,7
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;23,88
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;34,75
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;29,04
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;43,64
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;51,77
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;53,04
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;53,1
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;52,17
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;54,86
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;46,11
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;43,65
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;48,99
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;55,95
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;37,15
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;34,26
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;40,2
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;49,52
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;62,52
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;57,16
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;72,69
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;73,82
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;18,3
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;17,07
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;17,04
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;30,22
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;37,67
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;42,36
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;27,77
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;30,4
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;4,3
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;3,49
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;6,65
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;14,04
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;7,41
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;6,53
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;10,72
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;17,87
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;40,65
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;42,78
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;37,03
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;26,78
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;62,42
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;65,56
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;53,39
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;54,72
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;46,59
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;48,09
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;44,25
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;36,15
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;47,93
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;49,93
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;46,46
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;28,15
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;24,86
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;28,1
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;16,07
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;15,29
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;56,58
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;57,08
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;54,93
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;56,05
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;34,1
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;35,37
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;32,01
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;25,52
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;17,36
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;17,6
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;17,84
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;12,83
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;30,85
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;31,98
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;27,44
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;28,74
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;9,98
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;8,07
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;13,87
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;14,31
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.7 % of enterprises that purchased or accessed Big Data (4);Total;12,17
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;11,09
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;12,86
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;18,72
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.8 % enterprises with specific training in Big Data (4);Total;14,18
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;13,3
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;13,05
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.8 % enterprises with specific training in Big Data (4);250 or more;24,06
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.9 % enterprises with Big Data training provided by external providers (5);Total;86,32
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;84,9
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;88,56
3. Total Services (CNAE 45-82, excluding CNAE 56: food and drink services, CNAE 75 and financial services);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;89,18
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;8,6
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;6,88
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;16,38
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;30,49
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;6,24
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;4,82
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;12,68
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;24,41
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;31,88
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;25,39
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;42,58
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;49,77
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;45,83
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;43,98
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;49,6
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;48,66
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;46,25
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;45,85
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;43,87
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;57,09
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;30,68
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;30,03
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;25,04
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;54,08
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;58,57
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;54,1
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;68,97
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;61,08
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;8,73
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;5,93
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;10,36
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;25,98
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;43,13
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;49,37
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;27,77
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;42,26
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;3,44
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;2,86
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;5,42
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;15,16
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;6,66
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;6,08
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;9,35
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;18,07
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;51,31
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;55,65
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;39,2
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;18,07
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;70,87
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;74,31
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;58,45
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;55,55
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;49,38
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;50,64
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;48,63
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;29,17
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;55,98
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;58,69
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;51,29
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;24,17
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;31,16
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;35,26
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;16,1
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;13,91
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;48,2
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;44,33
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;64,32
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;57,42
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;38,37
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;39,9
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;36,36
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;17,99
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;13,3
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;10,89
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;25,55
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;10,45
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;35,27
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;39,02
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;18,65
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;30,21
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;10,34
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;6,39
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;19,79
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;15,37
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.7 % of enterprises that purchased or accessed Big Data (4);Total;8,31
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;7,81
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;6,69
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;18,25
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.8 % enterprises with specific training in Big Data (4);Total;6
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;5,42
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;4,23
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.8 % enterprises with specific training in Big Data (4);250 or more;17,19
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.9 % enterprises with Big Data training provided by external providers (5);Total;98,24
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;100
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;100
3.1. Sale and repair of motor vehicles, wholesale and retail (CNAE 45-47);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;91,69
3.2. Transport and storage (CNAE 49-53);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;13,99
3.2. Transport and storage (CNAE 49-53);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;13,04
3.2. Transport and storage (CNAE 49-53);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;16,34
3.2. Transport and storage (CNAE 49-53);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;31,45
3.2. Transport and storage (CNAE 49-53);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;11,39
3.2. Transport and storage (CNAE 49-53);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;10,42
3.2. Transport and storage (CNAE 49-53);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;14,4
3.2. Transport and storage (CNAE 49-53);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;25,97
3.2. Transport and storage (CNAE 49-53);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;37,58
3.2. Transport and storage (CNAE 49-53);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;33,64
3.2. Transport and storage (CNAE 49-53);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;43,74
3.2. Transport and storage (CNAE 49-53);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;69,29
3.2. Transport and storage (CNAE 49-53);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;93,24
3.2. Transport and storage (CNAE 49-53);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;94,84
3.2. Transport and storage (CNAE 49-53);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;90,83
3.2. Transport and storage (CNAE 49-53);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;80,09
3.2. Transport and storage (CNAE 49-53);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;19,76
3.2. Transport and storage (CNAE 49-53);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;15,93
3.2. Transport and storage (CNAE 49-53);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;30,72
3.2. Transport and storage (CNAE 49-53);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;35,65
3.2. Transport and storage (CNAE 49-53);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;20,79
3.2. Transport and storage (CNAE 49-53);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;15,62
3.2. Transport and storage (CNAE 49-53);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;38,14
3.2. Transport and storage (CNAE 49-53);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;34,75
3.2. Transport and storage (CNAE 49-53);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;58,63
3.2. Transport and storage (CNAE 49-53);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;55,53
3.2. Transport and storage (CNAE 49-53);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;72,79
3.2. Transport and storage (CNAE 49-53);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;55,76
3.2. Transport and storage (CNAE 49-53);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;15,28
3.2. Transport and storage (CNAE 49-53);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;14,8
3.2. Transport and storage (CNAE 49-53);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;15,94
3.2. Transport and storage (CNAE 49-53);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;19,48
3.2. Transport and storage (CNAE 49-53);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;28,31
3.2. Transport and storage (CNAE 49-53);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;29,67
3.2. Transport and storage (CNAE 49-53);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;18,54
3.2. Transport and storage (CNAE 49-53);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;40,13
3.2. Transport and storage (CNAE 49-53);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;4,46
3.2. Transport and storage (CNAE 49-53);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;4,17
3.2. Transport and storage (CNAE 49-53);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;4,83
3.2. Transport and storage (CNAE 49-53);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;11,46
3.2. Transport and storage (CNAE 49-53);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;3,92
3.2. Transport and storage (CNAE 49-53);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;2,76
3.2. Transport and storage (CNAE 49-53);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;7,72
3.2. Transport and storage (CNAE 49-53);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;25,76
3.2. Transport and storage (CNAE 49-53);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;23,99
3.2. Transport and storage (CNAE 49-53);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;21,67
3.2. Transport and storage (CNAE 49-53);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;28,01
3.2. Transport and storage (CNAE 49-53);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;26,05
3.2. Transport and storage (CNAE 49-53);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;71,79
3.2. Transport and storage (CNAE 49-53);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;81,13
3.2. Transport and storage (CNAE 49-53);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;59,72
3.2. Transport and storage (CNAE 49-53);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;55,35
3.2. Transport and storage (CNAE 49-53);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;47,48
3.2. Transport and storage (CNAE 49-53);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;55,2
3.2. Transport and storage (CNAE 49-53);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;41,85
3.2. Transport and storage (CNAE 49-53);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;25,32
3.2. Transport and storage (CNAE 49-53);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;57,82
3.2. Transport and storage (CNAE 49-53);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;64,99
3.2. Transport and storage (CNAE 49-53);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;54,41
3.2. Transport and storage (CNAE 49-53);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;33,65
3.2. Transport and storage (CNAE 49-53);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;7,21
3.2. Transport and storage (CNAE 49-53);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;0
3.2. Transport and storage (CNAE 49-53);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;19,89
3.2. Transport and storage (CNAE 49-53);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;13,29
3.2. Transport and storage (CNAE 49-53);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;44
3.2. Transport and storage (CNAE 49-53);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;40,08
3.2. Transport and storage (CNAE 49-53);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;51,18
3.2. Transport and storage (CNAE 49-53);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;46,77
3.2. Transport and storage (CNAE 49-53);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;39,47
3.2. Transport and storage (CNAE 49-53);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;46,06
3.2. Transport and storage (CNAE 49-53);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;29,69
3.2. Transport and storage (CNAE 49-53);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;30,34
3.2. Transport and storage (CNAE 49-53);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;25,67
3.2. Transport and storage (CNAE 49-53);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;32,92
3.2. Transport and storage (CNAE 49-53);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;20,13
3.2. Transport and storage (CNAE 49-53);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;5,31
3.2. Transport and storage (CNAE 49-53);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;38,53
3.2. Transport and storage (CNAE 49-53);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;45,6
3.2. Transport and storage (CNAE 49-53);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;27,94
3.2. Transport and storage (CNAE 49-53);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;28,9
3.2. Transport and storage (CNAE 49-53);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;16,08
3.2. Transport and storage (CNAE 49-53);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;17,43
3.2. Transport and storage (CNAE 49-53);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;10,86
3.2. Transport and storage (CNAE 49-53);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;12,86
3.2. Transport and storage (CNAE 49-53);F.7 % of enterprises that purchased or accessed Big Data (4);Total;8,67
3.2. Transport and storage (CNAE 49-53);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;9,89
3.2. Transport and storage (CNAE 49-53);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;1,77
3.2. Transport and storage (CNAE 49-53);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;12
3.2. Transport and storage (CNAE 49-53);F.8 % enterprises with specific training in Big Data (4);Total;11,26
3.2. Transport and storage (CNAE 49-53);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;12,6
3.2. Transport and storage (CNAE 49-53);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;5,08
3.2. Transport and storage (CNAE 49-53);F.8 % enterprises with specific training in Big Data (4);250 or more;10,87
3.2. Transport and storage (CNAE 49-53);F.9 % enterprises with Big Data training provided by external providers (5);Total;70,57
3.2. Transport and storage (CNAE 49-53);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;74,54
3.2. Transport and storage (CNAE 49-53);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;10,47
3.2. Transport and storage (CNAE 49-53);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;88,84
3.3. Accommodation services (CNAE 55);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;12,6
3.3. Accommodation services (CNAE 55);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;9,81
3.3. Accommodation services (CNAE 55);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;19,7
3.3. Accommodation services (CNAE 55);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;28,7
3.3. Accommodation services (CNAE 55);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;5,96
3.3. Accommodation services (CNAE 55);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;3,47
3.3. Accommodation services (CNAE 55);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;12,52
3.3. Accommodation services (CNAE 55);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;18,93
3.3. Accommodation services (CNAE 55);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;10,05
3.3. Accommodation services (CNAE 55);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;0
3.3. Accommodation services (CNAE 55);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;17,81
3.3. Accommodation services (CNAE 55);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;17,9
3.3. Accommodation services (CNAE 55);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;32,79
3.3. Accommodation services (CNAE 55);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;36,74
3.3. Accommodation services (CNAE 55);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;30,48
3.3. Accommodation services (CNAE 55);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;26,64
3.3. Accommodation services (CNAE 55);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;79,52
3.3. Accommodation services (CNAE 55);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;82,36
3.3. Accommodation services (CNAE 55);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;73,68
3.3. Accommodation services (CNAE 55);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;92,6
3.3. Accommodation services (CNAE 55);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;51,28
3.3. Accommodation services (CNAE 55);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;58,73
3.3. Accommodation services (CNAE 55);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;49,1
3.3. Accommodation services (CNAE 55);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;30,53
3.3. Accommodation services (CNAE 55);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;43,75
3.3. Accommodation services (CNAE 55);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;0
3.3. Accommodation services (CNAE 55);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;79,51
3.3. Accommodation services (CNAE 55);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;69,57
3.3. Accommodation services (CNAE 55);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;20,79
3.3. Accommodation services (CNAE 55);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;17,64
3.3. Accommodation services (CNAE 55);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;20,73
3.3. Accommodation services (CNAE 55);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;33,74
3.3. Accommodation services (CNAE 55);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;54,8
3.3. Accommodation services (CNAE 55);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;82,36
3.3. Accommodation services (CNAE 55);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;34,2
3.3. Accommodation services (CNAE 55);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;30,43
3.3. Accommodation services (CNAE 55);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;9,97
3.3. Accommodation services (CNAE 55);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;7,65
3.3. Accommodation services (CNAE 55);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;15,91
3.3. Accommodation services (CNAE 55);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;23,24
3.3. Accommodation services (CNAE 55);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;11,78
3.3. Accommodation services (CNAE 55);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;11,79
3.3. Accommodation services (CNAE 55);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;10,32
3.3. Accommodation services (CNAE 55);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;22,08
3.3. Accommodation services (CNAE 55);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;38,6
3.3. Accommodation services (CNAE 55);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;32,29
3.3. Accommodation services (CNAE 55);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;67,44
3.3. Accommodation services (CNAE 55);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;35,59
3.3. Accommodation services (CNAE 55);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;65,46
3.3. Accommodation services (CNAE 55);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;62,83
3.3. Accommodation services (CNAE 55);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;74,57
3.3. Accommodation services (CNAE 55);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;73,95
3.3. Accommodation services (CNAE 55);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;36,6
3.3. Accommodation services (CNAE 55);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;31,43
3.3. Accommodation services (CNAE 55);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;63,25
3.3. Accommodation services (CNAE 55);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;23,99
3.3. Accommodation services (CNAE 55);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;39,55
3.3. Accommodation services (CNAE 55);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;33,23
3.3. Accommodation services (CNAE 55);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;67,43
3.3. Accommodation services (CNAE 55);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;40,14
3.3. Accommodation services (CNAE 55);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;30,09
3.3. Accommodation services (CNAE 55);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;25,37
3.3. Accommodation services (CNAE 55);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;49,85
3.3. Accommodation services (CNAE 55);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;33,92
3.3. Accommodation services (CNAE 55);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;54,46
3.3. Accommodation services (CNAE 55);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;56,17
3.3. Accommodation services (CNAE 55);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;50,16
3.3. Accommodation services (CNAE 55);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;43,43
3.3. Accommodation services (CNAE 55);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;22,88
3.3. Accommodation services (CNAE 55);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;16,52
3.3. Accommodation services (CNAE 55);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;53,01
3.3. Accommodation services (CNAE 55);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;16,45
3.3. Accommodation services (CNAE 55);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;24,13
3.3. Accommodation services (CNAE 55);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;28,69
3.3. Accommodation services (CNAE 55);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;9,7
3.3. Accommodation services (CNAE 55);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;4,83
3.3. Accommodation services (CNAE 55);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;26,76
3.3. Accommodation services (CNAE 55);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;26,41
3.3. Accommodation services (CNAE 55);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;22,72
3.3. Accommodation services (CNAE 55);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;45,43
3.3. Accommodation services (CNAE 55);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;8,8
3.3. Accommodation services (CNAE 55);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;7,85
3.3. Accommodation services (CNAE 55);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;7,79
3.3. Accommodation services (CNAE 55);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;20,37
3.3. Accommodation services (CNAE 55);F.7 % of enterprises that purchased or accessed Big Data (4);Total;9,12
3.3. Accommodation services (CNAE 55);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;0
3.3. Accommodation services (CNAE 55);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;20,99
3.3. Accommodation services (CNAE 55);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;25,76
3.3. Accommodation services (CNAE 55);F.8 % enterprises with specific training in Big Data (4);Total;4,97
3.3. Accommodation services (CNAE 55);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;0
3.3. Accommodation services (CNAE 55);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;13,51
3.3. Accommodation services (CNAE 55);F.8 % enterprises with specific training in Big Data (4);250 or more;5
3.3. Accommodation services (CNAE 55);F.9 % enterprises with Big Data training provided by external providers (5);Total;100
3.3. Accommodation services (CNAE 55);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;.
3.3. Accommodation services (CNAE 55);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;100
3.3. Accommodation services (CNAE 55);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;100
3.4. Information and communications (CNAE 58-63);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;17,58
3.4. Information and communications (CNAE 58-63);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;14,23
3.4. Information and communications (CNAE 58-63);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;23,56
3.4. Information and communications (CNAE 58-63);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;48,03
3.4. Information and communications (CNAE 58-63);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;15,97
3.4. Information and communications (CNAE 58-63);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;13,19
3.4. Information and communications (CNAE 58-63);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;20,72
3.4. Information and communications (CNAE 58-63);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;42,16
3.4. Information and communications (CNAE 58-63);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;30,01
3.4. Information and communications (CNAE 58-63);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;18,14
3.4. Information and communications (CNAE 58-63);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;45,67
3.4. Information and communications (CNAE 58-63);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;59,23
3.4. Information and communications (CNAE 58-63);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;40,8
3.4. Information and communications (CNAE 58-63);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;32,75
3.4. Information and communications (CNAE 58-63);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;51,92
3.4. Information and communications (CNAE 58-63);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;59,48
3.4. Information and communications (CNAE 58-63);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;75,35
3.4. Information and communications (CNAE 58-63);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;80,81
3.4. Information and communications (CNAE 58-63);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;65,36
3.4. Information and communications (CNAE 58-63);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;67,78
3.4. Information and communications (CNAE 58-63);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;59,41
3.4. Information and communications (CNAE 58-63);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;62,11
3.4. Information and communications (CNAE 58-63);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;49,39
3.4. Information and communications (CNAE 58-63);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;66,28
3.4. Information and communications (CNAE 58-63);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;64,41
3.4. Information and communications (CNAE 58-63);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;56,62
3.4. Information and communications (CNAE 58-63);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;71,56
3.4. Information and communications (CNAE 58-63);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;90,1
3.4. Information and communications (CNAE 58-63);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;31,93
3.4. Information and communications (CNAE 58-63);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;32,91
3.4. Information and communications (CNAE 58-63);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;24,71
3.4. Information and communications (CNAE 58-63);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;41,95
3.4. Information and communications (CNAE 58-63);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;43,34
3.4. Information and communications (CNAE 58-63);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;51,17
3.4. Information and communications (CNAE 58-63);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;33,22
3.4. Information and communications (CNAE 58-63);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;23,69
3.4. Information and communications (CNAE 58-63);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;6,02
3.4. Information and communications (CNAE 58-63);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;4,68
3.4. Information and communications (CNAE 58-63);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;8,82
3.4. Information and communications (CNAE 58-63);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;16,55
3.4. Information and communications (CNAE 58-63);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;20,69
3.4. Information and communications (CNAE 58-63);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;20,46
3.4. Information and communications (CNAE 58-63);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;22,3
3.4. Information and communications (CNAE 58-63);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;16,77
3.4. Information and communications (CNAE 58-63);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;28,96
3.4. Information and communications (CNAE 58-63);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;31,84
3.4. Information and communications (CNAE 58-63);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;16,2
3.4. Information and communications (CNAE 58-63);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;38,56
3.4. Information and communications (CNAE 58-63);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;45,01
3.4. Information and communications (CNAE 58-63);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;48,17
3.4. Information and communications (CNAE 58-63);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;32,73
3.4. Information and communications (CNAE 58-63);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;41,14
3.4. Information and communications (CNAE 58-63);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;45,41
3.4. Information and communications (CNAE 58-63);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;47,19
3.4. Information and communications (CNAE 58-63);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;36,78
3.4. Information and communications (CNAE 58-63);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;57,67
3.4. Information and communications (CNAE 58-63);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;31,39
3.4. Information and communications (CNAE 58-63);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;32,53
3.4. Information and communications (CNAE 58-63);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;25,22
3.4. Information and communications (CNAE 58-63);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;44,4
3.4. Information and communications (CNAE 58-63);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;23,28
3.4. Information and communications (CNAE 58-63);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;27,66
3.4. Information and communications (CNAE 58-63);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;6,41
3.4. Information and communications (CNAE 58-63);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;16,87
3.4. Information and communications (CNAE 58-63);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;79,03
3.4. Information and communications (CNAE 58-63);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;84,05
3.4. Information and communications (CNAE 58-63);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;58,16
3.4. Information and communications (CNAE 58-63);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;84,74
3.4. Information and communications (CNAE 58-63);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;28,04
3.4. Information and communications (CNAE 58-63);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;30,15
3.4. Information and communications (CNAE 58-63);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;19,57
3.4. Information and communications (CNAE 58-63);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;27,82
3.4. Information and communications (CNAE 58-63);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;17,91
3.4. Information and communications (CNAE 58-63);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;19,92
3.4. Information and communications (CNAE 58-63);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;9,24
3.4. Information and communications (CNAE 58-63);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;22,65
3.4. Information and communications (CNAE 58-63);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;33,22
3.4. Information and communications (CNAE 58-63);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;31,9
3.4. Information and communications (CNAE 58-63);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;38,97
3.4. Information and communications (CNAE 58-63);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;29,38
3.4. Information and communications (CNAE 58-63);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;13,43
3.4. Information and communications (CNAE 58-63);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;14,29
3.4. Information and communications (CNAE 58-63);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;8,76
3.4. Information and communications (CNAE 58-63);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;18,96
3.4. Information and communications (CNAE 58-63);F.7 % of enterprises that purchased or accessed Big Data (4);Total;14,46
3.4. Information and communications (CNAE 58-63);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;10,9
3.4. Information and communications (CNAE 58-63);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;18,74
3.4. Information and communications (CNAE 58-63);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;23,14
3.4. Information and communications (CNAE 58-63);F.8 % enterprises with specific training in Big Data (4);Total;34,23
3.4. Information and communications (CNAE 58-63);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;28,44
3.4. Information and communications (CNAE 58-63);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;43,58
3.4. Information and communications (CNAE 58-63);F.8 % enterprises with specific training in Big Data (4);250 or more;43,33
3.4. Information and communications (CNAE 58-63);F.9 % enterprises with Big Data training provided by external providers (5);Total;75,25
3.4. Information and communications (CNAE 58-63);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;61,84
3.4. Information and communications (CNAE 58-63);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;94,14
3.4. Information and communications (CNAE 58-63);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;79,06
3.5. Real estate activities (CNAE 68);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;8,5
3.5. Real estate activities (CNAE 68);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;5,37
3.5. Real estate activities (CNAE 68);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;41,74
3.5. Real estate activities (CNAE 68);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;25,95
3.5. Real estate activities (CNAE 68);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;5,83
3.5. Real estate activities (CNAE 68);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;3,45
3.5. Real estate activities (CNAE 68);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;30,84
3.5. Real estate activities (CNAE 68);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;20,34
3.5. Real estate activities (CNAE 68);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;23,83
3.5. Real estate activities (CNAE 68);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;4,98
3.5. Real estate activities (CNAE 68);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;48,96
3.5. Real estate activities (CNAE 68);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;22,06
3.5. Real estate activities (CNAE 68);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;44,34
3.5. Real estate activities (CNAE 68);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;23,01
3.5. Real estate activities (CNAE 68);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;71,08
3.5. Real estate activities (CNAE 68);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;54,66
3.5. Real estate activities (CNAE 68);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;37,44
3.5. Real estate activities (CNAE 68);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;14,12
3.5. Real estate activities (CNAE 68);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;70,18
3.5. Real estate activities (CNAE 68);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;23,28
3.5. Real estate activities (CNAE 68);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;73,69
3.5. Real estate activities (CNAE 68);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;80,91
3.5. Real estate activities (CNAE 68);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;65,04
3.5. Real estate activities (CNAE 68);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;67,4
3.5. Real estate activities (CNAE 68);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;35,94
3.5. Real estate activities (CNAE 68);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;14,12
3.5. Real estate activities (CNAE 68);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;55,87
3.5. Real estate activities (CNAE 68);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;100
3.5. Real estate activities (CNAE 68);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;7,22
3.5. Real estate activities (CNAE 68);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;0
3.5. Real estate activities (CNAE 68);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;14,69
3.5. Real estate activities (CNAE 68);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;22,06
3.5. Real estate activities (CNAE 68);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;67,45
3.5. Real estate activities (CNAE 68);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;85,88
3.5. Real estate activities (CNAE 68);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;52,46
3.5. Real estate activities (CNAE 68);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;0
3.5. Real estate activities (CNAE 68);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;3,91
3.5. Real estate activities (CNAE 68);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;1,92
3.5. Real estate activities (CNAE 68);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;25,08
3.5. Real estate activities (CNAE 68);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;14,58
3.5. Real estate activities (CNAE 68);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;3,86
3.5. Real estate activities (CNAE 68);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;2,95
3.5. Real estate activities (CNAE 68);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;18,7
3.5. Real estate activities (CNAE 68);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;13,64
3.5. Real estate activities (CNAE 68);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;13,79
3.5. Real estate activities (CNAE 68);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;6,15
3.5. Real estate activities (CNAE 68);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;28,82
3.5. Real estate activities (CNAE 68);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;55,56
3.5. Real estate activities (CNAE 68);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;91,54
3.5. Real estate activities (CNAE 68);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;92,43
3.5. Real estate activities (CNAE 68);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;87,22
3.5. Real estate activities (CNAE 68);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;100
3.5. Real estate activities (CNAE 68);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;50,64
3.5. Real estate activities (CNAE 68);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;47,76
3.5. Real estate activities (CNAE 68);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;58,41
3.5. Real estate activities (CNAE 68);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;55,56
3.5. Real estate activities (CNAE 68);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;62,53
3.5. Real estate activities (CNAE 68);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;58,38
3.5. Real estate activities (CNAE 68);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;87,22
3.5. Real estate activities (CNAE 68);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;0
3.5. Real estate activities (CNAE 68);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;0
3.5. Real estate activities (CNAE 68);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;0
3.5. Real estate activities (CNAE 68);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;0
3.5. Real estate activities (CNAE 68);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;0
3.5. Real estate activities (CNAE 68);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;26,97
3.5. Real estate activities (CNAE 68);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;13,76
3.5. Real estate activities (CNAE 68);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;52,71
3.5. Real estate activities (CNAE 68);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;100
3.5. Real estate activities (CNAE 68);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;81,06
3.5. Real estate activities (CNAE 68);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;93,85
3.5. Real estate activities (CNAE 68);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;47,29
3.5. Real estate activities (CNAE 68);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;55,56
3.5. Real estate activities (CNAE 68);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;0
3.5. Real estate activities (CNAE 68);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;0
3.5. Real estate activities (CNAE 68);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;0
3.5. Real estate activities (CNAE 68);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;0
3.5. Real estate activities (CNAE 68);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;19,2
3.5. Real estate activities (CNAE 68);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;7,57
3.5. Real estate activities (CNAE 68);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;47,29
3.5. Real estate activities (CNAE 68);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;55,56
3.5. Real estate activities (CNAE 68);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;11,05
3.5. Real estate activities (CNAE 68);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;0
3.5. Real estate activities (CNAE 68);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;25,93
3.5. Real estate activities (CNAE 68);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;25,55
3.5. Real estate activities (CNAE 68);F.7 % of enterprises that purchased or accessed Big Data (4);Total;19,4
3.5. Real estate activities (CNAE 68);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;0
3.5. Real estate activities (CNAE 68);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;45,8
3.5. Real estate activities (CNAE 68);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;42,84
3.5. Real estate activities (CNAE 68);F.8 % enterprises with specific training in Big Data (4);Total;28,83
3.5. Real estate activities (CNAE 68);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;35,28
3.5. Real estate activities (CNAE 68);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;17,19
3.5. Real estate activities (CNAE 68);F.8 % enterprises with specific training in Big Data (4);250 or more;42,84
3.5. Real estate activities (CNAE 68);F.9 % enterprises with Big Data training provided by external providers (5);Total;90,15
3.5. Real estate activities (CNAE 68);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;100
3.5. Real estate activities (CNAE 68);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;56,25
3.5. Real estate activities (CNAE 68);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;100
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;12,5
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;10,75
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;18,86
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;30,96
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;9,79
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;8,2
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;15,16
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;28,5
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;49,23
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;41,63
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;69,17
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;58,72
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;28,9
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;22,5
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;41,65
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;47,95
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;48,23
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;47,05
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;49,73
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;54,13
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;50,94
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;49,89
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;55,51
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;47,24
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;78,65
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;79,26
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;75,75
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;81,44
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;31,38
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;31,94
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;29,9
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;30,68
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;29,46
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;30,92
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;26,87
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;24,29
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;4,19
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;3,42
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;7,35
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;10,49
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;10,04
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;7,91
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;19,41
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;34
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;28,79
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;27,15
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;34,92
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;22,09
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;49,55
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;52,01
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;42,6
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;51,89
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;34,09
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;34,1
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;31,86
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;41,72
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;41,68
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;46,24
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;34,43
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;26,59
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;11
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;11,32
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;8,48
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;16,93
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;54,64
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;59,65
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;42,31
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;53,07
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;24,83
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;22,93
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;25,95
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;37,67
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;10,45
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;7,25
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;16,05
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;19,2
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;20,17
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;14,04
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;34,28
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;25,44
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;3,94
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;1,09
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;11,96
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;7,86
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.7 % of enterprises that purchased or accessed Big Data (4);Total;19,59
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;18,87
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;19,65
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;26,76
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.8 % enterprises with specific training in Big Data (4);Total;19,77
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;18,31
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;18,27
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.8 % enterprises with specific training in Big Data (4);250 or more;39,22
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.9 % enterprises with Big Data training provided by external providers (5);Total;94,81
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;94,69
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;97,97
3.6. Professional, scientific and technical activities (excl. veterinary) (CNAE 69-74);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;90,77
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;6,27
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;4,91
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;7,12
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;20,11
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;4,88
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;3,87
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;5,47
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;15,35
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;32,15
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;34,3
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;18,69
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;40,99
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;71,02
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;89,02
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;35,11
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;56,83
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;37,29
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;31,69
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;41,96
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;49,2
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;22,28
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;6,36
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;47,64
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;42,21
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;64,08
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;51,02
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;82,38
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;83,32
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;13,95
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;11,13
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;6,25
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;31,5
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;31,89
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;39,67
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;22,6
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;18,59
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;3,72
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;2,97
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;3,8
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;12,62
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;3,41
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;2,66
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;4,97
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;8,51
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;65,1
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;74,96
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;56,43
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;39,18
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;77,14
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;84,96
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;72,74
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;51,15
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;78,02
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;94,19
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;58,85
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;46,46
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;61,13
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;66,61
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;68,39
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;20,23
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;44,46
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;62,73
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;23,15
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;7,96
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;69,31
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;77,32
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;57,45
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;58,8
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;52,81
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;67,5
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;38,32
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;17,71
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;42
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;59,1
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;18,74
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;15,12
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;28,56
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;34,34
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;20,01
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;21,02
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;4,11
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;0
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;8,12
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;11,78
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.7 % of enterprises that purchased or accessed Big Data (4);Total;18,17
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;21,74
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;15,02
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;11,1
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.8 % enterprises with specific training in Big Data (4);Total;19,59
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;24,95
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;4,53
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.8 % enterprises with specific training in Big Data (4);250 or more;20,82
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.9 % enterprises with Big Data training provided by external providers (5);Total;95,57
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;100
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;14,02
3.7. Administrative and support service activities (incl. travel agencies) (CNAE 77-82);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;100
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;Total;16,62
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 10 to 49;15,01
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;From 50 to 249;16,2
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise;250 or more;45,92
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1 % enterprises that  performed Big Data analysis neither by its own employees;Total;15,48
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 10 to 49;14,16
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1 % enterprises that  performed Big Data analysis neither by its own employees;From 50 to 249;14,76
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1 % enterprises that  performed Big Data analysis neither by its own employees;250 or more;41,41
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);Total;40,22
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 10 to 49;30,64
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);From 50 to 249;58,14
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1);250 or more;64,04
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);Total;43,82
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 10 to 49;34,83
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);From 50 to 249;65,16
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1);250 or more;58,2
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);Total;70,03
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 10 to 49;77,29
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);From 50 to 249;51,49
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1);250 or more;60,73
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);Total;63,56
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 10 to 49;68,57
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);From 50 to 249;47,06
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1);250 or more;63,68
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);Total;73,49
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 10 to 49;69,13
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);From 50 to 249;79,35
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.2.A % of enterprises that analyzed Big Data by Machine Learning (1);250 or more;88,38
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);Total;34,42
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 10 to 49;35,86
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);From 50 to 249;27,62
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1);250 or more;38,05
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);Total;40,83
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 10 to 49;47,08
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);From 50 to 249;27,36
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1);250 or more;28,45
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;Total;5,11
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 10 to 49;5,01
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;From 50 to 249;3,79
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company;250 or more;13,33
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);Total;17,38
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 10 to 49;17,2
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);From 50 to 249;18,12
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2);250 or more;16,54
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );Total;22,17
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 10 to 49;23,02
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );From 50 to 249;18,63
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 );250 or more;28,29
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);Total;35,33
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 10 to 49;32,51
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);From 50 to 249;45,89
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3);250 or more;24,66
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);Total;34,89
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 10 to 49;32,84
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);From 50 to 249;40,19
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.C % of enterprises that did not perform Big Data analysis by insufficient sources of Big Data that would be needed to perform the analysis (3);250 or more;46,95
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);Total;24,78
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 10 to 49;19,39
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);From 50 to 249;41,56
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3);250 or more;32,99
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);Total;14,06
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 10 to 49;14,61
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);From 50 to 249;13,27
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3);250 or more;5,74
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);Total;73,37
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 10 to 49;77,29
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);From 50 to 249;60,37
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3);250 or more;74,09
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);Total;14,14
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 10 to 49;10,46
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);From 50 to 249;26,6
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3);250 or more;11,18
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);Total;22,51
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 10 to 49;26,54
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);From 50 to 249;10,54
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3);250 or more;11,64
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);Total;35,36
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 10 to 49;35,02
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);From 50 to 249;37,31
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.5.H % of enterprises that did not perform Big Data analysis by other factors (3);250 or more;28,24
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);Total;13,03
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 10 to 49;12,5
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);From 50 to 249;12,48
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4);250 or more;16,96
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.7 % of enterprises that purchased or accessed Big Data (4);Total;14,85
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.7 % of enterprises that purchased or accessed Big Data (4);From 10 to 49;12,05
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.7 % of enterprises that purchased or accessed Big Data (4);From 50 to 249;19,73
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.7 % of enterprises that purchased or accessed Big Data (4);250 or more;21,81
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.8 % enterprises with specific training in Big Data (4);Total;35,14
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.8 % enterprises with specific training in Big Data (4);From 10 to 49;29,84
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.8 % enterprises with specific training in Big Data (4);From 50 to 249;45,93
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.8 % enterprises with specific training in Big Data (4);250 or more;45,62
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.9 % enterprises with Big Data training provided by external providers (5);Total;73,96
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.9 % enterprises with Big Data training provided by external providers (5);From 10 to 49;64,35
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.9 % enterprises with Big Data training provided by external providers (5);From 50 to 249;91,33
4. Sector ICT (261-264, 268, 465, 582, 61, 6201, 6202, 6203, 6209, 631, 951);F.9 % enterprises with Big Data training provided by external providers (5);250 or more;78,2