Once loaded, you can query the "Gold" layer to answer business questions.
A data warehouse typically uses a , consisting of a central Fact Table (quantitative data like sales) surrounded by Dimension Tables (descriptive data like products or dates). Building a Data Warehouse with Examples in SQL ...
-- Finding total sales by product category SELECT p.category, SUM(s.sale_amount) AS total_revenue FROM fact_sales s JOIN dim_product p ON s.product_key = p.product_key GROUP BY p.category; Use code with caution. Copied to clipboard Once loaded, you can query the "Gold" layer
-- Transforming and Loading: Standardizing product names to uppercase INSERT INTO dim_product (product_key, product_name, category) SELECT product_id, UPPER(p_name), category FROM raw_staging_products; Use code with caution. Copied to clipboard 4. The Final View (Analytical Querying) category) SELECT product_id
: Stores metrics like price, quantity, and foreign keys.
