About This Architecture

Gold Layer Sales Data Warehouse implements a classic star schema with FACT_SALES at the center connected to four dimensions: DIM_CUSTOMERS (360-degree customer view with cohort analysis), DIM_PRODUCTS (SCD Type 2 tracking historical product changes), and DIM_DATE (role-playing dimension for order, ship, and due dates). The fact table captures transactional metrics including quantity, unit_price, total_sales, product_cost, and calculated profit, with strategic indexes on customer_sk, product_sk, order_date_sk, and order_number for query performance. This schema enables comprehensive business analytics across revenue, profit, customer segmentation, product performance, and sales trends while maintaining data quality through surrogate keys and natural key tracking. Fork and customize this diagram on Diagrams.so to adapt the schema for your specific business metrics and dimensional requirements. The SCD Type 2 implementation on products ensures audit trails for pricing and product line changes over time.

People also ask

How do you design a star schema for a sales data warehouse with customer analytics and product history tracking?

This gold layer star schema centers on FACT_SALES connected to DIM_CUSTOMERS (with cohort analysis), DIM_PRODUCTS (SCD Type 2 for historical changes), and DIM_DATE (role-playing for multiple date contexts). It enables revenue, profit, customer segmentation, and product performance analytics while maintaining data quality through surrogate and natural keys.

Gold Layer Sales Data Warehouse Star Schema

Autointermediatedata-warehousestar-schemadimensional-modelinganalyticsSCD-Type-2business-intelligence
Domain: Data EngineeringAudience: data engineers and analytics engineers designing enterprise data warehouses
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Created by

August 20, 2026

Updated

September 14, 2026 at 11:32 AM

Type

er

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