Database normalization is a process used to organize data in a database. It helps in reducing redundancy and improving data integrity. This guide will help you understand the basics of database normalization.
Normalization Levels
Database normalization is divided into several levels, known as normal forms. Each normal form addresses a specific type of redundancy and improves data integrity.
First Normal Form (1NF)
- Attributes: All attributes in a table must contain atomic values (values that cannot be divided further).
- Example: A table with a primary key and no repeating groups.
Second Normal Form (2NF)
- 1NF: The table must be in 1NF.
- Non-Prime Attributes: All non-prime attributes must be fully functionally dependent on the primary key.
Third Normal Form (3NF)
- 2NF: The table must be in 2NF.
- Transitive Dependency: There should be no transitive dependency, meaning that a non-prime attribute should not be functionally dependent on another non-prime attribute.
Benefits of Normalization
- Reduces Redundancy: By eliminating redundancy, normalization helps in reducing storage requirements.
- Improves Data Integrity: Normalization ensures that data is consistent and accurate.
- Easier Maintenance: Normalized databases are easier to maintain and modify.
Example
Let's consider a table with the following attributes: Order ID, Customer Name, Customer Address, and Product Name.
This table has redundancy because if a customer places multiple orders, the customer's address will be repeated for each order.
To normalize this table, we can split it into two tables:
Orders Table:
- Order ID (Primary Key)
- Customer ID (Foreign Key)
Customers Table:
- Customer ID (Primary Key)
- Customer Name
- Customer Address
By normalizing the data, we have reduced redundancy and improved data integrity.
For more information on database normalization, you can visit our Database Design guide.