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Rapid Recall 01–20

Answer from memory before opening the key.

  1. Define Big Data in the chapter's useful sense.
  2. Define Data Science in Chapter 14.
  3. Why is “Big” relative?
  4. Name the six V's.
  5. Volume vs Velocity?
  6. Variety/Variability vs Viscosity?
  7. Volatility vs Veracity?
  8. Name the four context-diagram goals.
  9. Name the nine context-diagram activities.
  10. Name the seven Data Science process phases.
  11. Why are the nine-activity and seven-step lists not contradictory?
  12. What does descriptive analytics ask?
  13. What does predictive analytics ask?
  14. What does prescriptive analytics ask?
  15. What is the chapter's rear-view vs windshield contrast?
  16. ETL vs ELT?
  17. Why can ELT suit a Big Data environment?
  18. What is a data lake?
  19. What makes a lake become a swamp?
  20. What should be captured at ingestion to prevent context loss?

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