Data Warehousing
Dimensional modelling, facts, dimensions and slowly changing history.
4 notes · all topicsWarehousing & lakehouse
Start here · beginner2
- 1OLTP vs OLAP: Why Analytics Needs a Different DatabaseRow stores vs column stores, normalized vs dimensional schemas, and why you do not run dashboards on the production database.2 min
- 2Data Quality Checks That Catch Real IncidentsFreshness, volume, schema, uniqueness, nulls and referential integrity — what to check, where to check it, and what to do when a check fails.3 min
Next · intermediate2
- 3Kimball vs Inmon vs Data VaultThe three classic warehouse design approaches, what each optimises for, and how modern teams combine them.2 min
- 4Slowly Changing Dimensions Type 2, Explained HonestlySurrogate keys, validity intervals, and the difference between observed history and true source history.2 min
