Mastering SELECT Query with Operators (Arithmetic, Conditional), LIKE, GROUP BY, HAVING, LIMIT MySQL

Description:
This topic is designed to give you a complete understanding of how to use the powerful SELECT statement in SQL by combining different types of operators and clauses that are widely used in real-world database queries.

You will start by learning how to use Arithmetic Operators (+, -, *, /) inside a SELECT query to perform calculations on numeric columns, such as calculating total salary, discounts, or profit directly from the database.

Next, you will explore Conditional Operators like along with logical operators such as AND, OR, and NOT. These are used with the WHERE clause to filter data based on specific conditions—for example, retrieving employees with salary greater than a certain amount or filtering records based on multiple conditions.

Then, you will understand how to use the LIKE operator for pattern searching. This helps you find data based on partial matches using wildcards like % (multiple characters) and _ (single character), which is extremely useful when working with names, emails, or text fields.

Moving forward, the topic covers GROUP BY, which is used to group rows that have the same values in specified columns. This is commonly used with aggregate functions like COUNT(), SUM(), AVG(), MAX(), and MIN() to generate summarized reports.

After grouping the data, you will learn about the HAVING clause, which allows you to filter grouped results. Unlike WHERE, which filters rows before grouping, HAVING filters data after aggregation—making it essential for conditions on grouped data.

Finally, you will explore LIMIT and OFFSET, which are used to control the number of records returned and to implement pagination. LIMIT restricts the number of rows, while OFFSET skips a specific number of rows—useful for displaying data page by page in applications.

By the end of this topic, you will be able to write advanced SQL queries that combine multiple clauses and operators effectively. This knowledge is crucial for data analysis, reporting, and backend development, and is widely used in databases like MySQL, PostgreSQL, and SQL Server (with slight variations).