What is stored procedure?

A stored procedure is a precompiled collection of SQL statements that performs a specific task or set of tasks. It is stored in a database and can be called and executed many times without the need to rewrite the SQL statements each time. Stored procedures are often used for tasks such as data manipulation, data validation, and business logic implementation within a database. They can improve performance, security, and maintainability of database operations.

When use stored procedure?

Stored procedures are often used in relational database management systems (RDBMS) such as MySQL, PostgreSQL, SQL Server, and Oracle. As a data analyst, stored procedures can be useful in several scenarios:

Data processing: Stored procedures can be used for complex data processing tasks, such as transforming, aggregating, and validating data within the database, which can help streamline data analysis workflows.
Business logic implementation: Stored procedures can encapsulate business logic within the database, making it easier to maintain and update the logic without impacting the application layer.

Should You Learn it?

As companies favor high-performance databases over traditional RDBMS more and more, the importance of stored procedures is decreasing. In today's fast-paced tech world, Python's versatility and functionality offer a strong alternative to using stored procedures. With Python and tools like Apache Airflow, tasks that were traditionally done with stored procedures can now be carried out efficiently, making stored procedures less necessary in modern database management.

The image shows the Google Trends data for the term stored procedure in the United States over the past five years. There is a clear pattern of decreasing interest in this topic.