🚀 SQL Roadmap 2026 — Part 5

Aggregate Functions: COUNT, SUM, AVG, MIN & MAX 📊

So far, you've learned how to retrieve, filter, and sort individual rows.

Now we're moving to one of the most important skills for a Data Analyst:

Turning thousands of rows into meaningful business metrics.

For example:

How many customers do we have?

What is our total revenue?

What is the average order value?

What is the highest salary?

What is the lowest product price?

That's exactly what aggregate functions are designed for.

1️⃣ What Are Aggregate Functions?

Aggregate functions perform a calculation across multiple rows and return a summarized result.

The five essential functions are:

• COUNT() Counts rows/values

• SUM() Calculates total

• AVG() Calculates average

• MIN() Finds minimum

• MAX() Finds maximum

2️⃣ COUNT()

COUNT() is used to count records or non-NULL values.

Count all rows:

SELECT COUNT(*) AS total_customers
FROM customers;

If there are 5,000 customers: total_customers = 5000

3️⃣ COUNT(*) vs COUNT(column)

This distinction is extremely important.

COUNT(*) Counts rows.

SELECT COUNT(*)
FROM employees;

COUNT(column) Counts non-NULL values in that column.

SELECT COUNT(manager_id)
FROM employees;

Suppose: employee A | 101, B | 102, C | NULL, D | 103

Then: COUNT(*) = 4, COUNT(manager_id) = 3

Because one manager_id is NULL.

Interview Tip:

COUNT(*) counts rows; COUNT(column) counts non-NULL values in that column.

4️⃣ COUNT(DISTINCT)

Use COUNT(DISTINCT ...) when you want to count unique values.

Example:

SELECT
    COUNT(DISTINCT customer_id) AS unique_customers
FROM orders;

Suppose: customer_id 101, 101, 102, 103, 103, 103

Then: COUNT(*) = 6, COUNT(DISTINCT customer_id) = 3

This is extremely common in analytics.

5️⃣ Real-World Example: Active Customers

Suppose your orders table contains thousands of orders.

The business asks:

How many unique customers placed an order?

SELECT
    COUNT(DISTINCT customer_id) AS active_customers
FROM orders;

Notice that we're counting customers, not orders. One customer may have placed 20 orders, but should still count as one unique customer.

6️⃣ SUM()

SUM() calculates the total of a numeric column.

Example:

SELECT
    SUM(amount) AS total_revenue
FROM orders;

If the amounts are: 1000, 2000, 1500, 3000 then: SUM = 7500

7️⃣ SUM With a Condition

You can combine SUM() with WHERE.

Example:

Calculate revenue from completed orders only.

SELECT
    SUM(amount) AS completed_revenue
FROM orders
WHERE order_status = 'Completed';

This is a very common business query.

8️⃣ AVG()

AVG() calculates the average of non-NULL numeric values.

Example:

SELECT
    AVG(salary) AS average_salary
FROM employees;

If salaries are: 50000, 60000, 70000 then: Average = 60000

9️⃣ AVG and NULL Values

AVG() generally ignores NULL values.

Suppose: salary 50000, 60000, NULL, 70000

The average is: (50000 + 60000 + 70000) / 3 = 60000

It doesn't divide by 4. This is important when working with incomplete real-world data.

🔟 MIN()

MIN() finds the smallest value.

Example:

SELECT
    MIN(salary) AS lowest_salary
FROM employees;

For products: