Can you define normalization in the database context?

Normalization in a database context is the process of efficiently organising data to reduce redundancy and improve data integrity.

In more detail, normalization is a systematic approach of decomposing tables to eliminate data redundancy and undesirable characteristics like Insertion, Update and Deletion Anomalies. It is a multi-step process that puts data into tabular form by removing duplicated data from the relation tables. Normalization is used for mainly two purposes, eliminating redundant (useless) data and ensuring data dependencies make sense i.e. data is logically stored.

The process of normalization involves dividing a database into two or more tables and defining relationships between the tables. The end result is that redundant data is eliminated, and only data related to the attribute (column) is stored within the table. This helps to safeguard the database in a way that it satisfies all the levels of normalization forms.

There are several levels of normalization, also referred to as normal forms, each with a higher level of rigor. First Normal Form (1NF) sets the very basic rules for an organised database: eliminate duplicative columns from the same table, create separate tables for each group of related data and identify each set of related data with a primary key. Second Normal Form (2NF) further addresses the concept of removing duplicative data: meet all the rules of the first normal form and remove subsets of data that apply to multiple rows of a table and place them in separate tables. Third Normal Form (3NF) goes one large step further: meet all the rules of the second normal form and remove columns that are not dependent upon the primary key.

In essence, the main goal of database normalization is to minimise data redundancy, which in turn helps to minimise disk storage space and to ensure consistency in the data. This process is an essential part of any successful database design.