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3. Analytics that forecasts what will happen.
5. Analytics that summarizes what happened.
9. Measure of how accurate, complete and consistent data is.
14. Field focused on analyzing historical data to support business decisions.
16. The usefulness or benefit gained from analysing data.
17. Practice of ensuring data consistency, quality, availability and security.
19. Analytics that explains why something happened.
20. The practice of using data and analysis to improve business performance.
23. science. Use algorithms machine learning and production
26. Data that follows a defined format or schema.
27. Actionable understanding derived from data analysis.
28. The simulation of human intelligence by machines.
30. Professional who identifies business problems and proposes improvements.
31. Field involving algorithms and machine learning to predict trends and behaviours.

1. Analytics that suggests what should be done next.
2. Measures to safeguard data from unauthorized access or breaches.
4. The amount of data generated (one of the 5 Vs).
6. Professional who examines datasets to draw quantitative conclusions.
7. Protection of personal or sensitive data from misuse.
8. The use of data, statistical methods, and technology to uncover insights.
10. Data without a predefined format.
11. The accuracy and trustworthiness of data.
12. Raw, unprocessed facts and figures.
13. The speed at which data is generated and processed.
15. A subset of AI that enables systems to learn from data automatically.
18. Understanding or awareness gained from information.
21. California law giving consumers rights over their personal data.
22. The different types and formats of data (structured, unstructured etc.).
24. European regulation governing data protection and privacy.
25. Discipline focused on identifying business needs and recommending solutions.
29. Processed data that has meaning.