Results by Autonomous Community ICT in companies with 10 or more employees (first quarter of 2020) by branch of economic activity

Big Data Analysis

Units:percentage

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- Autonomous communities and cities
  Values that contain
- Main variables
  Values that contain
  
  Selected:1
  
  Total:24
- Economic activity cluster
  Values that contain
  
  Selected:1
  
  Total:4

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	Economic activity cluster
Autonomous communities and cities Main variables	.	.	.
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Notes
- 1) The codes at the beginning of each literal refer to the corresponding question of the questionnaire or the section from which they are taken
  2) main variables:
  (1) Percentage of total enterprises that performed Big Data analysis with their own employees
  (2) Percentage of total enterprises that not performed Big Data analysis neither by its own employees nor by other enterprises or organizations
  (3) Percentage of total enterprises that did not perform Big Data analysis but considered doing so (4) Percentage of total enterprises that performed Big Data analysis neither by its own employees nor by other enterprises or organizations
  (1) Percentage of all companies with specific training in Big Data
  
  The symbol '..' means that the data are not published in compliance with statistical confidentiality
  The symbol '.' means that no information exists

Total: 0seriesy 0cells

Source:National Statistics Institute

F.1-3 % of enterprises that analyzed large data sources (Big Data) for their enterprise with their employees or through an external enterprise
F.1 % enterprises that performed Big Data analysis neither by its own employees
F.1.A % of enterprises that analyzed Big Data by source type: data using sensors or smart devices (1)
F.1.B % of enterprises that analyzed Big Data by source type: geolocation data from wearable devices (1)
F.1.C % of enterprises that analyzed Big Data by source type: data generated by social media (1)
F.1.D % of enterprises that analyzed Big Data by source type: other Big Data sources (1)
F.2.A % of enterprises that analyzed Big Data by Machine Learning (1)
F.2.B % of enterprises that analyzed Big Data by Natural language processing (NLP), natural language generation (NGL) or speech recognition (1)
F.2.C % of enterprises that analyzed Big Data by other Big Data analysis methods (1)
F.3 % of enterprises where a company or organisation other than their own analysed Big Data for their company
F.4 % of enterprises that did not perform Big Data analysis but considered doing so (2)
F.5.A % of enterprises that did not perform Big Data analysis by the cost seems too high compared to the benefits (3 )
F.5.B % of enterprises that did not perform Big Data analysis by human resources, skills or staff profiles are insufficient (3)
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)
F.5.D % of enterprises that did not perform Big Data analysis by insufficient ICT infrastructure (3)
F.5.E % of enterprises that did not perform Big Data analysis by difficulty in complying with privacy laws (3)
F.5.F % of enterprises that did not perform Big Data analysis by not a priority for the company (3)
F.5.G % of enterprises that did not perform Big Data analysis by insufficient quality of Big Data sources (3)
F.5.H % of enterprises that did not perform Big Data analysis by Big Data analysis is not useful for the company (3)
F.5.H % of enterprises that did not perform Big Data analysis by other factors (3)
F.6 % of enterprises that sold or gave access to its own Big Data to another company or organisation (4)
F.7 % of enterprises that purchased or accessed Big Data (4)
F.8 % enterprises with specific training in Big Data (4)
F.9 % enterprises with Big Data training provided by external providers (5)