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