Normalization and Denormalization

Databases serve as organized repositories, storing and retrieving data electronically for various applications.

Behind the scenes, Database Management Systems (DBMS) act as the gateway, enabling users and applications to interact with the database seamlessly.

At the heart of data organization lies the concept of a Data Model—a sophisticated abstraction that arranges data elements and defines their relationships.

In essence, Data Modeling is the art and science of crafting data models tailored to the needs of an information system.

Normalization​

Normalization is the process of organizing data in a database to reduce redundancy and dependency. It aims to eliminate data anomalies and ensure data integrity by breaking down large tables into smaller, related tables. It involves splitting data into multiple tables and establishing relationships between them using primary and foreign keys.

Denormalization​

Is the process of adding redundant data to a database to improve read performance or simplify queries. It aims to optimize query performance by reducing the need for joins and aggregations, especially in read-heavy applications. It involves duplicating data across tables or combining multiple tables into one to minimize the need for joins.