A large database defined as a single relation may result in data duplication. This repetition of data may result in:
So to handle these problems, we should analyze and decompose the relations with redundant data into smaller, simpler, and well-structured relations that are satisfy desirable properties. Normalization is a process of decomposing the relations into relations with fewer attributes.
The main reason for normalizing the relations is removing these anomalies. Failure to eliminate anomalies leads to data redundancy and can cause data integrity and other problems as the database grows. Normalization consists of a series of guidelines that helps to guide you in creating a good database structure.
Data modification anomalies can be categorized into three types:
Normalization works through a series of stages called Normal forms. The normal forms apply to individual relations. The relation is said to be in particular normal form if it satisfies constraints.
Following are the various types of Normal forms:

| Normal Form | Description |
|---|---|
| 1NF | A relation is in 1NF if it contains an atomic value. |
| 2NF | A relation will be in 2NF if it is in 1NF and all non-key attributes are fully functional dependent on the primary key. |
| 3NF | A relation will be in 3NF if it is in 2NF and no transition dependency exists. |
| BCNF | A stronger definition of 3NF is known as Boyce Codd's normal form. |
| 4NF | A relation will be in 4NF if it is in Boyce Codd's normal form and has no multi-valued dependency. |
| 5NF | A relation is in 5NF. If it is in 4NF and does not contain any join dependency, joining should be lossless. |
It is a sequence of steps called normal forms, used to ensure that data anomalies are introduced into the data when information is inserted, updated, or deleted.

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