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5. Analytics that explains why something happened.
6. Analytics that suggests what should be done next.
7. The accuracy and trustworthiness of data.
12. Field focused on analyzing historical data to support business decisions.
14. Data that follows a defined format or schema.
17. The different types and formats of data (structured, unstructured etc.).
18. European regulation governing data protection and privacy.
21. Practice of ensuring data consistency, quality, availability and security.
22. Raw, unprocessed facts and figures.
25. Field involving algorithms and machine learning to predict trends and behaviours.
27. The speed at which data is generated and processed.
28. Data without a predefined format.
29. The practice of using data and analysis to improve business performance.
30. California law giving consumers rights over their personal data.

1. Professional who examines datasets to draw quantitative conclusions.
2. The amount of data generated (one of the 5 Vs).
3. Measures to safeguard data from unauthorized access or breaches.
4. A subset of AI that enables systems to learn from data automatically.
8. The use of data, statistical methods, and technology to uncover insights.
9. Professional who identifies business problems and proposes improvements.
10. Understanding or awareness gained from information.
11. Analytics that summarizes what happened.
13. Analytics that forecasts what will happen.
15. analysis. Analytics that explains why something happened
16. The simulation of human intelligence by machines.
17. The usefulness or benefit gained from analysing data.
19. Protection of personal or sensitive data from misuse.
20. Discipline focused on identifying business needs and recommending solutions.
23. Actionable understanding derived from data analysis.
24. Processed data that has meaning.
26. Measure of how accurate, complete and consistent data is.