Database normalization is a data design and organization process applied to data structures based on rules that help building relational databases. In relational database design, the process of organizing data to minimize redundancy is called normalization. Normalization usually involves dividing a database into two or more tables and defining relationships between the tables. The objective is to isolate data so that additions, deletions, and modifications of a field can be made in just one table and then propagated through the rest of the database via the defined relationships.
1NF: Eliminate Repeating Groups
Make a separate table for each set of related attributes, and give each table a primary key. Each field contains at most one value from its attribute domain.
2NF: Eliminate Redundant Data
If an attribute depends on only part of a multi-valued key, remove it to a separate table.
3NF: Eliminate Columns Not Dependent On Key
If attributes do not contribute to a description of the key, remove them to a separate table. All attributes must be directly dependent on the primary key. (Read More Here)
BCNF: Boyce-Codd Normal Form
If there are non-trivial dependencies between candidate key attributes, separate them out into distinct tables.
4NF: Isolate Independent Multiple Relationships
No table may contain two or more 1:n or n:m relationships that are not directly related.
5NF: Isolate Semantically Related Multiple Relationships
There may be practical constrains on information that justify separating logically related many-to-many relationships.
ONF: Optimal Normal Form
A model limited to only simple (elemental) facts, as expressed in Object Role Model notation.
DKNF: Domain-Key Normal Form
A model free from all modification anomalies is said to be in DKNF.
Remember, these normalization guidelines are cumulative. For a database to be in 3NF, it must first fulfill all the criteria of a 2NF and 1NF database.
Normalization is one of the most frequently asked questions in interview questions and answers. You can read more about that over here.