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Data Warehouse Modeling Basics

Model analytics data well

Modeling a warehouse means choosing a clear grain, using dimensional models with fact and dimension tables, handling slowly changing dimensions, and enforcing surrogate keys and data quality checks.

Set Grain

Define the event/row meaning; keep it consistent.

Build Facts/Dimensions

Use surrogate keys; separate measures from descriptors.

Handle Change

Choose SCD types; validate keys and referential integrity.

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