SQL (Structured Query Language) is the lingua franca of data stored in relational databases. This lesson covers the core building blocks for analytics: SELECT, JOIN, GROUP BY, and HAVING, with practical examples and tips for business use-cases.
Most production data lives in relational databases (OLTP) or warehouses (OLAP). SQL lets analysts extract, transform, and aggregate that data efficiently. Mastering SELECT, JOIN, GROUP BY and HAVING enables you to answer questions like: “Which products drove revenue last quarter?” or “Which customers have high lifetime value?”
The SELECT clause picks which columns or expressions to return. Use it to compute KPIs directly in SQL.
-- Top 10 products by revenue
SELECT product_id, product_name, SUM(sales_amount) AS total_revenue
FROM sales
WHERE sales_date BETWEEN '2025-01-01' AND '2025-03-31'
GROUP BY product_id, product_name
ORDER BY total_revenue DESC
LIMIT 10;
Tip: alias metrics (AS total_revenue) so downstream reports use friendly names.