Across
- 3. Analytics to forecast what will happen.
- 4. Analytics type that summarises what happened.
- 5. Central storage that consolidates data from different sources
- 7. Process of removing errors, duplications and inconsistencies from data
- 10. Online Analytical Processing – multi-dimensional analysis
- 13. Unsupervised method grouping similar observations together.
- 16. Statement to be tested statistically
- 17. Consideration of fairness, bias and rights in analytics.
- 20. Type of analysis that explores data without preconceived hypothesis.
- 21. Analytics that delve into why something happened
- 24. Analytics type that recommends actions.
- 25. Deep understanding derived from data and analytics.
- 27. In R you might use subset(), cbind(), rbind() to do this
- 28. Displaying data in charts, graphs to help understand.
Down
- 1. Splitting customers into groups based on behaviour
- 2. Programming environment frequently used in analytics (starts with R)
- 5. Measure of how good the data is (accuracy, completeness)
- 6. Process and tools to convert raw data into meaningful business contexts
- 8. Branch of analytics involving algorithms like SVM, neural networks
- 9. Huge volume, velocity and variety of data
- 11. A modelling technique to support choices among alternatives.
- 12. Relationship modelling between dependent and independent variables
- 14. A measurable value that demonstrates how effectively a company is achieving key business objectives.
- 15. Predicting future values from past series.
- 18. Technique of selecting a subset from the population for analysis
- 19. Right to keep data secure and handle it responsibly.
- 22. Language used for querying relational databases.
- 23. Vectors, lists, data frames are examples
- 24. Another high-level programming language commonly used for analytics.
- 26. Visual interface summarising KPIs and metrics