Which of the following is NOT a valid aggregate function in SQL?

Understanding SQL Aggregate Functions

When working with SQL (Structured Query Language), we often use aggregate functions to perform calculations on a set of values to return a single scalar result. In this lesson, we're going to focus on the correct choice from this question: Which of the following is NOT a valid aggregate function in SQL?

Among the given options, SUM(), MAX(), and COUNT() are valid and commonly used SQL aggregate functions. However, AVERAGE() is not a valid aggregate function in SQL. The correct syntax to find the average value in SQL is AVG(), not AVERAGE().

Let's look at how these functions typically work in SQL.

AVG() Function

AVG() is an aggregate function that calculates the average of selected database entries. It works on numerical data types and returns a float value representing the average. A simple usage might look like this:

SELECT AVG(salary) 
FROM employees;

Here we're averaging all the values in the salary column from the employees table.

SUM(), COUNT(), MAX() Functions

Meanwhile, SUM(), COUNT(), and MAX() are also valid and widely accepted SQL aggregate functions.

  • SUM() is used to calculate the total sum of a numeric column.
  • COUNT() is used to count the number of rows in a select statement.
  • MAX() is used to find the maximum value in a set of values.

Here's an example for better understanding:

SELECT SUM(salary), COUNT(employee_id), MAX(salary) 
FROM employees;

In this example, SUM(salary) will give the total amount of salary paid to employees, COUNT(employee_id) will return the number of employees, and MAX(salary) will show the highest salary paid.

Conclusion

While working with SQL database queries, it's essential to remember the correct syntax and usage of aggregate functions. They are powerful tools in manipulating data and providing analytical insights. But remember, AVERAGE() is not among them; instead, you should use AVG() to calculate average values. It's these small details that can make a huge difference when working with SQL.

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