👥 SQL GROUP BY – Summarize Data with Aggregates

🧲 Introduction – What is GROUP BY in SQL?

The GROUP BY clause in SQL is used to group rows based on one or more columns and perform aggregate functions like SUM(), AVG(), COUNT(), etc. It’s essential for summarizing and reporting grouped data.

🎯 In this guide, you’ll learn:

• Syntax and structure of GROUP BY
• Use cases with COUNT, SUM, AVG, etc.
• Best practices and multiple column grouping

✅ 1. GROUP BY Syntax

SELECT column, AGG_FUNCTION(column)
FROM table
GROUP BY column;

✅ Groups the result set and performs aggregate calculations on each group.

📊 2. Example – Total Orders by Customer

SELECT customer_id, COUNT(*) AS total_orders
FROM orders
GROUP BY customer_id;

✅ Shows how many orders each customer has placed.

🧠 3. GROUP BY Multiple Columns

SELECT region, product, SUM(sales) AS total_sales
FROM sales_data
GROUP BY region, product;

✅ Breaks down sales by region and product combination.

🔄 4. GROUP BY with Filtering (WHERE + HAVING)

SELECT department, AVG(salary) AS avg_salary
FROM employees
WHERE salary > 0
GROUP BY department
HAVING AVG(salary) > 50000;

✅ Use WHERE to pre-filter rows and HAVING to filter grouped results.

🧩 5. GROUP BY and NULL Values

• NULL values are treated as a single group.

SELECT category, COUNT(*)
FROM products
GROUP BY category;

✅ NULL categories are grouped together.

📘 Best Practices

📌 Summary – Recap & Next Steps

GROUP BY makes it easy to summarize large data sets by category. It’s a core SQL tool for analytics and reporting.

🔍 Key Takeaways:

• Use GROUP BY with aggregate functions like COUNT, SUM, AVG
• Combine with HAVING to filter grouped results
• Supports grouping on multiple columns

⚙️ Real-World Relevance:
Used in reporting tools, dashboards, KPIs, invoice summaries, and log analysis.

➡️ Next: Learn about HAVING, ROLLUP, and CUBE for deeper data summaries.

❓ FAQ – SQL GROUP BY

❓ What is the use of GROUP BY?

✅ To group rows by one or more columns for aggregate operations.

❓ Can I use GROUP BY without an aggregate function?

❌ No. GROUP BY is useful only when paired with aggregate functions.

❓ What happens to NULLs in GROUP BY?

✅ They are treated as a group.

❓ Can I group by multiple columns?

✅ Yes, using a comma-separated list: GROUP BY col1, col2