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3. Measures to safeguard data from unauthorized access or breaches.
5. A subset of AI that enables systems to learn from data automatically.
6. The different types and formats of data (structured, unstructured etc.).
9. The amount of data generated (one of the 5 Vs).
13. The simulation of human intelligence by machines.
16. Data without a predefined format.
17. Field involving algorithms and machine learning to predict trends and behaviours.
18. Understanding or awareness gained from information.
19. The practice of using data and analysis to improve business performance.
21. Protection of personal or sensitive data from misuse.
23. Field focused on analyzing historical data to support business decisions.
24. The accuracy and trustworthiness of data.
25. European regulation governing data protection and privacy.
26. Raw, unprocessed facts and figures.
27. Analytics that suggests what should be done next.
28. Professional who identifies business problems and proposes improvements.
29. Forecasts possible future outcomes.
30. Professional who examines datasets to draw quantitative conclusions.

1. Actionable understanding derived from data analysis.
2. Measure of how accurate, complete and consistent data is.
4. Data that follows a defined format or schema.
6. The speed at which data is generated and processed.
7. Analytics that summarizes what happened.
8. Analytics that explains why something happened.
10. Discipline focused on identifying business needs and recommending solutions.
11. The usefulness or benefit gained from analysing data.
12. Practice of ensuring data consistency, quality, availability and security.
14. Analytics that forecasts what will happen.
15. The use of data, statistical methods, and technology to uncover insights.
20. California law giving consumers rights over their personal data.
22. Processed data that has meaning.