Data Analytics

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;

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