This produces a compact business summary.
For example:
Total_Sales: 15,000,000, Average_Sales: 75,000, Minimum_Sales: 1,000, Maximum_Sales: 500,000, Total_Orders: 200
🔟 Why Do We Need GROUP BY?
Aggregate functions give you an overall summary.
But what if the business asks:
"What are total sales for each region?"
You need to divide the data into groups.
That's what GROUP BY does.
1️⃣1️⃣ Basic GROUP BY
Suppose:
North: 50,000 and 70,000 → Total 120,000
South: 40,000 and 60,000 → Total 100,000
West: 80,000 → Total 80,000
Query:
SELECT
Region,
SUM(Sales) AS Total_Sales
FROM Orders
GROUP BY Region;
Result:
North = 120,000, South = 100,000, West = 80,000
Now you've answered:
"How much did each region sell?"
1️⃣2️⃣ GROUP BY Department
Suppose you have:
John - IT - 75,000
Sarah - HR - 60,000
Mike - IT - 82,000
David - Finance - 90,000
Alice - HR - 65,000
Query:
SELECT
Department,
AVG(Salary) AS Average_Salary
FROM Employees
GROUP BY Department;
Result:
Finance: 90,000, HR: 62,500, IT: 78,500
1️⃣3️⃣ GROUP BY with COUNT()
Question:
How many employees are in each department?
SELECT
Department,
COUNT(*) AS Employee_Count
FROM Employees
GROUP BY Department;
Result:
IT: 2, HR: 2, Finance: 1
1️⃣4️⃣ GROUP BY with Multiple Columns
You can group by more than one column.
Suppose your sales data contains:
North Electronics: 80,000
North Furniture: 40,000
South Electronics: 70,000
South Furniture: 50,000
Query:
SELECT
Region,
Category,
SUM(Sales) AS Total_Sales
FROM Orders
GROUP BY Region, Category;
Result:
North Electronics = 80,000, North Furniture = 40,000, South Electronics = 70,000, South Furniture = 50,000
This lets you analyze combinations of dimensions.
1️⃣5️⃣ GROUP BY vs PivotTable
This is an important connection.
In Excel:
Region → Rows
Sales → Values
In SQL:
SELECT
Region,
SUM(Sales)
FROM Orders
GROUP BY Region;
The analytical concept is very similar.
You're grouping records and calculating an aggregate.
1️⃣6️⃣ HAVING
Now suppose you want:
"Show only regions where total sales are greater than ₹100,000."
You can't simply use WHERE on the aggregate result.
You use: HAVING
SELECT
Region,
SUM(Sales) AS Total_Sales
FROM Orders
GROUP BY Region
HAVING SUM(Sales) > 100000;
Result:
North = 120,000
1️⃣7️⃣ WHERE vs HAVING
This is a very common SQL interview question.
WHERE
Filters individual rows before grouping.
Example:
SELECT *
FROM Orders
WHERE Region = 'North';
HAVING
Filters groups after aggregation.
Example:
SELECT
Region,
SUM(Sales) AS Total_Sales
FROM Orders
GROUP BY Region
HAVING SUM(Sales) > 100000;
Remember:
WHERE → Filter rows
HAVING → Filter groups
1️⃣8️⃣ WHERE + GROUP BY + HAVING
You can use all three.
Question:
Find regions where 2026 sales exceed ₹100,000.
Conceptually:
SELECT
Region,
SUM(Sales) AS Total_Sales
FROM Orders
WHERE Order_Date >= '2026-01-01'
AND Order_Date < '2027-01-01'
GROUP BY Region
HAVING SUM(Sales) > 100000;
