SQL Tutorial | Mastering the IN Operator, Aggregate Functions, DISTINCT, and Aliases 🎓
SQL Tutorial: Mastering the IN Operator, Aggregate Functions, DISTINCT, and Aliases 🎓
In this video, we’ll take an in-depth look at some of the most essential SQL commands to help you write efficient queries and extract meaningful data from your database. Whether you’re a beginner or looking to sharpen your SQL skills, this tutorial covers it all. Let’s dive into the four key SQL concepts you'll learn today:
1️⃣ IN Operator:
The IN operator allows you to filter data by specifying multiple values in a WHERE clause. It helps simplify complex queries that would otherwise require multiple OR conditions. We’ll show you how to:
Use IN to filter records by matching values within a list.
Apply the IN operator with subqueries to work with dynamic lists of values.
2️⃣ Aggregate Functions:
Aggregate functions are essential when working with large datasets, as they help you summarize data. We’ll explore:
SUM(): Calculate the total sum of a numeric column.
AVG(): Find the average value of a numeric column.
COUNT(): Count the number of rows that match a condition.
MAX() and MIN(): Identify the highest and lowest values in a column.
You’ll learn how to use these functions both in simple queries and combined with other SQL features.
3️⃣ DISTINCT Function:
Duplicate data is a common issue in databases, but with the DISTINCT keyword, you can easily return only unique values in your result set. We’ll demonstrate how to:
Use DISTINCT to remove duplicate records.
Combine DISTINCT with aggregate functions to get unique insights.
4️⃣ Aliases (AS Keyword):
Aliases in SQL allow you to temporarily rename tables or columns to make your queries more readable and your output more understandable. You’ll see:
How to use column aliases to give friendly names to the output columns.
How table aliases can simplify complex queries involving multiple tables.
By the end of this video, you’ll be able to confidently use the IN operator, aggregate functions, DISTINCT, and aliases in your SQL queries to improve performance and readability.
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