[Verse 1] Meet Sarah, she's building a warehouse for her company's data store Customer info scattered everywhere, sales figures by the score She needs a structure that makes sense, organizes what she's got Star schema is her answer, it's the perfect central spot [Chorus] In the center sits the fact table, measuring what we do Sales amounts and quantities, transactions coming through Around it shine dimension tables, context for each row Who bought it, when they bought it, that's how the insights flow [Verse 2] Facts are numbers that we measure, revenue and counts and such Dimensions give the story, the who and when and where we touch Customer table holds the names, product table shows what's sold Time dimension tracks the moments when these stories unfold [Chorus] In the center sits the fact table, measuring what we do Sales amounts and quantities, transactions coming through Around it shine dimension tables, context for each row Who bought it, when they bought it, that's how the insights flow [Verse 3] But Sarah's data gets complex, customers move and change their names Snowflake schema breaks it down, normalizes all the claims Product categories split apart, geography gets its own space Looks like snowflake with its branches, each table finds its place [Bridge] Slowly changing dimensions, that's the tricky part to see Type one overwrites the old, type two keeps history Type three adds a column for both current and before Choose your method carefully, depends what you're looking for [Chorus] In the center sits the fact table, measuring what we do Sales amounts and quantities, transactions coming through Around it shine dimension tables, context for each row Who bought it, when they bought it, that's how the insights flow [Outro] Star for speed and simple queries, snowflake saves you space Both will serve your warehouse well, just know their proper place Facts and dimensions working together, slowly changing through time Data warehouse architecture, now you know the design
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