Q.Which aggregate function in SQL returns the smallest value from a column in a table ? (A) MIN() (B) MAX() (C) SMALL() (D) LOWER()

Imagine you have a giant box of receipts from a month of sales at a small shop. You don't want to look at every single receipt one by one — you want a single, useful number that summarises the whole pile. How much total money came in? What was the average sale? How many customers bought something? That instinct — to collapse a pile of raw details into one meaningful number — is exactly what an SQL aggregate function does.

In a database, a table might hold thousands of rows of data: one row for every sale, every student, every product. An aggregate function takes all those rows in a column and boils them down to a single value. It doesn't change the data; it answers a question about the whole set. The most common ones are COUNT, SUM, AVG, MIN, and MAX. Each one has a clear, everyday meaning.

COUNT tells you how many rows there are — like counting how many students are in a class list. SUM adds up all the numbers in a column — like totalling the marks of every student in an exam. AVG gives the average of those numbers. MIN and MAX find the smallest and largest values — the lowest temperature recorded or the highest sale of the day.

The real power comes when you combine them with the GROUP BY clause. Without GROUP BY, an aggregate function summarises the entire table. With GROUP BY, you split the table into groups first, then apply the function to each group separately. Think of it like this: you don't just want the average sale for the whole year — you want the average sale per month. GROUP BY month creates twelve groups, and AVG(sale_amount) runs once for each group, giving you twelve averages.

This is why aggregate functions matter in business, economics, and any data-driven decision. A manager doesn't ask "what was every single transaction?" They ask "what was the total revenue last quarter?" or "which product category had the highest average rating?" Aggregate functions turn raw, overwhelming data into actionable summaries. …