Data Query Language (DQL) is a subset of SQL (Structured Query Language) that focuses on retrieving data from relational databases. Unlike Data Definition Language (DDL) and Data Manipulation Language (DML), which define and modify database structures and data, DQL is primarily concerned with fetching and presenting data in a structured manner.
The SELECT statement is the cornerstone of DQL and is used to retrieve data based on specified criteria. Understanding DQL is essential for anyone working with databases, as it enables efficient data extraction, filtering, and reporting.
The SELECT statement is used to retrieve data from one or more tables. Its basic syntax is as follows:
SELECT column1, column2, ... FROM table_name WHERE condition;
SELECT * FROM employees;
SELECT first_name, last_name, department FROM employees;
SELECT * FROM employees WHERE department = 'Sales';
SELECT * FROM employees ORDER BY salary DESC;
SELECT DISTINCT department FROM employees;
SELECT COUNT(*) FROM employees; SELECT AVG(salary) FROM employees; SELECT SUM(salary) FROM employees WHERE department = 'IT';
SELECT department, COUNT(*) FROM employees GROUP BY department;
SELECT department, AVG(salary) FROM employees GROUP BY department HAVING AVG(salary) > 50000;
SELECT employees.first_name, employees.last_name, departments.department_name FROM employees JOIN departments ON employees.department_id = departments.id;
SELECT first_name, last_name FROM employees WHERE department_id = (SELECT id FROM departments WHERE department_name = 'HR');
DQL plays a crucial role in SQL, enabling users to extract meaningful insights from databases. Mastering SELECT statements, filtering, sorting, aggregation, joins, and subqueries will significantly enhance your ability to query and analyze data efficiently. By following best practices, you can ensure optimal query performance and maintainable database operations.
By understanding and utilizing DQL effectively, data professionals can unlock the full potential of SQL databases for business intelligence, reporting, and decision-making.
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