WHERE Clause in SQL Server

WHERE Clause in SQL Server

Introduction:
The WHERE clause is an essential part of SQL queries that allows you to filter data from a database table based on specified conditions. It is used in conjunction with SELECT, UPDATE, DELETE, and other SQL statements to fetch or manipulate specific rows that meet the specified criteria.

Syntax:
The basic syntax of the WHERE clause is as follows:

sql
SELECT column1, column2, ...
FROM table_name
WHERE condition;

Explanation:

• SELECT: Specifies the columns you want to retrieve from the table.
• FROM: Specifies the table from which data will be retrieved.
• WHERE: Contains the condition that determines which rows to include in the result set.

Examples:

1. Retrieve data based on a single condition:

sql
SELECT * 
FROM employees
WHERE department = 'HR';

Explanation: This query retrieves all columns from the "employees" table where the "department" column has a value of 'HR'.

2. Retrieve data based on multiple conditions:

sql
SELECT * 
FROM orders
WHERE status = 'Shipped' AND total_amount > 1000;

Explanation: This query retrieves all columns from the "orders" table where the "status" column is 'Shipped' and the "total_amount" column is greater than 1000.

3. Using logical operators with the WHERE clause:

sql
SELECT * 
FROM products
WHERE category = 'Electronics' OR stock_quantity > 50;

Explanation: This query retrieves all columns from the "products" table where the "category" column is 'Electronics' or the "stock_quantity" column is greater than 50.

4. Combining AND and OR operators:

sql
SELECT * 
FROM customers
WHERE (city = 'New York' AND age > 30) OR (city = 'Los Angeles' AND age > 25);

Explanation: This query retrieves all columns from the "customers" table where the customer is either from New York and older than 30, or from Los Angeles and older than 25.

Conclusion:
The WHERE clause is a powerful feature in SQL Server that allows you to retrieve specific data from a table based on conditions. By using logical operators and combining multiple conditions, you can create complex queries to filter and manipulate data effectively.