Database normalization is the process of organizing data in a database to reduce redundancy and improve efficiency. It involves breaking down larger tables into smaller ones and ensuring that each table only contains data that is relevant to a single entity. The primary goal of normalization is to eliminate data redundancy, which can lead to inconsistencies and errors in data.
Normalization is typically divided into several normal forms, each of which has specific rules for how data should be organized. The most common normal forms are:
- First Normal Form (1NF): In 1NF, all columns in a table are atomic, meaning they contain only one piece of data. For example, a customer’s name and address should be stored in separate columns.
- Second Normal Form (2NF): In 2NF, all non-key columns in a table are fully dependent on the primary key. This means that any columns that do not depend on the primary key should be moved to a separate table.
- Third Normal Form (3NF): In 3NF, all non-key columns in a table are independent of each other. This means that any columns that are related to each other should be moved to a separate table.
There are additional normal forms beyond 3NF, but they are less commonly used. Normalization is an iterative process, and it may be necessary to go back and revise the database design multiple times to achieve the desired level of normalization.
Overall, normalization is an important part of database design because it helps to eliminate data redundancy, improve data consistency, and reduce the risk of data inconsistencies and errors.
