Understanding Normalization:

Normalization is a fundamental concept in database design that helps organize and structure data efficiently while minimizing redundancy and maintaining data integrity. In this blog, we'll delve into the world of normalization in the context of PostgreSQL,

What is Normalization?

Normalization is the process of organizing a database to reduce redundancy and dependency among data while ensuring data integrity. It involves breaking down large tables into smaller

Normalization offers several benefits:

1. Data Integrity: By minimizing redundancy, data inconsistencies are reduced, and the chances of errors are minimized.
2. Storage Efficiency: Normalized databases occupy less storage space as compared to denormalized databases.
3. Flexibility: Changes to data are easier to implement since modifications are required in fewer places.
4. Maintainability: The structure of the database becomes more intuitive and manageable.
5. Query Performance: In some cases, normalized databases can improve query performance by reducing the amount of data that needs to be retrieved and joined.

Levels of Normalization: Normalization is divided into several levels, each building upon the previous one. The most commonly used levels are:

1. First Normal Form (1NF): Each column contains only atomic (indivisible) values. No repeating groups or arrays are allowed.
2. Second Normal Form (2NF): Meets 1NF and has no partial dependencies. In other words, attributes depend on the entire primary key, not just a part of it.
3. Third Normal Form (3NF): Meets 2NF and has no transitive dependencies. Attributes depend only on the primary key and not on other non-key attributes.