Volume 3: The Modern Frontier: Scale, Intelligence, and What Comes Next2/10
  1. 01Systems at Scale 201-210
  2. 02Modern Data Systems 211-220
  3. 03Machine Learning 221-230
  4. 04Generative AI Systems 231-240
  5. 05Security and Privacy 241-250
  6. 06Emerging Computing 251-260
  7. 07Technology and Society 261-270
  8. 08Digital Economics 271-280
  9. 09Responsible Futures 281-290
  10. 10Synthesis 291-300

Chapter 02 of 10

Modern Data Systems 211-220

10 lessons53 min readingParts 211-220
  1. 01Data WarehousesWhy do organizations copy operational data into a separate analytical system?6 min read
  2. 02Data LakesWhat is gained by storing large amounts of raw or lightly processed data?6 min read
  3. 03ETL and ELTWhen should data be transformed before or after loading into an analytical system?5 min read
  4. 04Batch and Stream ProcessingShould data be processed in groups or continuously as events arrive?5 min read
  5. 05Event Time and Processing TimeWhich clock matters when events arrive late or out of order?5 min read
  6. 06Data QualityWhat makes a dataset trustworthy enough for decisions?5 min read
  7. 07Data LineageHow can a team trace where a dashboard number came from?5 min read
  8. 08Data GovernanceWho decides how important organizational data may be used?6 min read
  9. 09Analytics and Causal QuestionsWhy does a pattern in data not automatically explain what caused it?5 min read
  10. 10A/B TestingHow can a product compare two experiences fairly?5 min read