Data Warehousing & Modelling

Build practical foundations in Data Warehousing & Modelling.

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Syllabus

Part 1

  1. Why warehouses exist
  2. Operational versus analytical data
  3. ETL and ELT
  4. Facts and dimensions
  5. Grain of a table

Part 2

  1. Star schemas
  2. Snowflake schemas
  3. Slowly changing dimensions
  4. Surrogate keys
  5. Date and time dimensions

Part 3

  1. Data quality checks
  2. Incremental loading
  3. Partitioning and clustering
  4. Data lineage
  5. Metadata and catalogues

Part 4

  1. Building a sales model
  2. Choosing measures
  3. Query performance
  4. Cost control
  5. Access control and privacy

Part 5

  1. Testing a data model
  2. Common modelling mistakes
  3. Documenting metrics
  4. Interview questions
  5. Data warehousing revision checklist