Database normalization is a process in database design that aims to organize and structure data in a way that reduces redundancy and dependency. The goal is to minimize data anomalies and improve data integrity. This is achieved by breaking down a large table into smaller, related tables and defining relationships between them.

The normalization process typically involves applying a series of rules or forms, often represented by normal forms (such as First Normal Form, Second Normal Form, Third Normal Form, etc.). Each normal form builds upon the previous one, introducing additional constraints to ensure that data is stored in a structured and efficient manner.

Here are the first three normal forms briefly explained:

• First Normal Form (1NF): Ensures that each column in a table contains atomic (indivisible) values, and there are no repeating groups or arrays.
• Second Normal Form (2NF): Extends 1NF by ensuring that each non-key attribute is fully functionally dependent on the primary key. In simpler terms, it eliminates partial dependencies.
• Third Normal Form (3NF): Builds upon 2NF by removing transitive dependencies. It ensures that non-key attributes are not dependent on other non-key attributes.

By following these normalization principles, a database designer can reduce the chances of data anomalies, such as update anomalies, insertion anomalies, and deletion anomalies. Normalized databases are often more flexible, scalable, and maintainable, making it easier to adapt to changing business requirements.

Check the video below for further understanding of normalisation