Database normalization is a process that helps to minimize data redundancy and dependency in a database by breaking down large and complex databases into smaller, more manageable ones. Normalization ensures that information is stored in databases accurately and logically, preventing any duplication of data and inconsistencies.
There are different levels of normalization or normal forms, which include:
1. First Normal Form (1NF): The first normal form requires that there should be no repeating groups of data and that each column should have a unique name. For example, a table of customers should avoid having multiple columns for phone numbers, instead, have a separate phone number table.
2. Second Normal Form (2NF): The second normal form requires that every non-key attribute is fully dependent on the primary key. This means that a table with a composite primary key where some fields are not dependent on the primary key should be split into two separate tables.
3. Third Normal Form (3NF): The third normal form eliminates transitive dependencies, meaning that there should be no non-key attributes that depend on another attribute that is not part of the primary key. If a table contains data that can be derived from another table already in the database, it should be moved to that table instead.
4. Fourth Normal Form (4NF): The fourth normal form requires that a table does not contain multiple independent multi-valued facts about an entity. In other words, if a table contains combinations of data that can create multiple relationships and contradictions, it should be split into separate tables.
5. Fifth Normal Form (5NF) or Domain-Key Normal Form (DK/NF): The fifth normal form is the highest level of normalization, and it requires that a table does not contain any join dependencies or join keys. It means that sometimes two tables may have the same relationship through an intermediate table, and this intermediate table should be eliminated.
Normalization helps to ensure data accuracy and consistency, speed up query processing times, and reduce data redundancy in the overall database. However, over-normalizing a database can also lead to performance problems, so it’s important to strike a balance between normalization and performance optimization.