To use multiple aggregation functions with the GROUP BY clause in SQL, you first need to know what aggregation functions are.

Aggregation functions like SUM(), AVG(), COUNT(), MAX(), and MIN() help you do calculations on a group of numbers and give you just one result. They are really useful for summarizing information, especially when paired with the GROUP BY clause. This clause groups rows that have the same values in certain columns, so you can see the aggregated data.

Why and How to Use Multiple Aggregation Functions:

1. Why Combine Functions?

   • To get useful insights from your data.
   • To look at different parts of the data at the same time.
   • For example, if you combine SUM() with COUNT(), you can see the total sales and the number of transactions in one go.

2. Basic Structure: Here’s what an SQL query looks like when you combine different aggregation functions:

   SELECT column1, 
          COUNT(column2) AS CountColumn,
          SUM(column3) AS SumColumn,
          AVG(column4) AS AvgColumn
   FROM table_name
   GROUP BY column1;
   

3. Example: Imagine you have a Sales table with columns like ProductID, QuantitySold, and SalePrice. If you want to find out how many items were sold and their total price per product, you can use this:

   SELECT ProductID, 
          COUNT(QuantitySold) AS TotalSales,
          SUM(SalePrice) AS TotalRevenue
   FROM Sales
   GROUP BY ProductID;
   

   In this example:

   • COUNT(QuantitySold) tells you how many sales were made for each product.
   • SUM(SalePrice) adds up all the money made from sales of each product.

4. Things to Remember:

   • Every column in the SELECT statement that isn’t part of an aggregation function must be listed in the GROUP BY clause.
   • This helps make sure your results make sense, as each aggregated value connects to the correct group.

5. Mixing Different Functions: You can use different types of aggregation functions in a single query to analyze your data in various ways. But the more functions and groups you add, the more complex the SQL statement can get.

By using multiple aggregation functions with GROUP BY, you can neatly summarize large sets of data and get important information that helps you make better decisions in your database work.