Building A Data Warehouse With Examples In Sql ... Online

Once loaded, you can query the "Gold" layer to answer business questions.

: Cleaning data in the Silver Layer , such as standardizing "Yes/No" strings to booleans. Load : Inserting into the final Gold Layer tables.

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 ...

moves data from raw sources (like CSVs or ERP systems) into your warehouse. Extract : Pulling raw data into the Bronze Layer .

: Stores metrics like price, quantity, and foreign keys. Once loaded, you can query the "Gold" layer

-- 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

: dim_product , dim_customer , and dim_date provide context. 2. Laying the Foundation (SQL Table Creation) You start by defining these structures in your database. A data warehouse typically uses a , consisting

-- Creating a Dimension Table for Products CREATE TABLE dim_product ( product_key INT PRIMARY KEY, product_name VARCHAR(100), category VARCHAR(50) ); -- Creating the Fact Table CREATE TABLE fact_sales ( sale_id INT PRIMARY KEY, product_key INT, customer_key INT, sale_amount DECIMAL(10, 2), sale_date DATE, FOREIGN KEY (product_key) REFERENCES dim_product(product_key) ); Use code with caution. Copied to clipboard 3. Moving the Earth (ETL Process)