-- 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
: Stores metrics like price, quantity, and foreign keys. Building a Data Warehouse with Examples in SQL ...
To build a data warehouse, you first need to identify your business objectives, such as revenue forecasting or customer segmentation, to guide your design. A common approach is the , which organizes data into three layers: Bronze (raw), Silver (cleaned), and Gold (analytical/star schema). The Story: Building the "North Star" Sales Warehouse 1. Designing the Blueprint (Data Modeling) -- Finding total sales by product category SELECT p
-- 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) A common approach is the , which organizes
moves data from raw sources (like CSVs or ERP systems) into your warehouse. Extract : Pulling raw data into the Bronze Layer .
