How does data normalization work?

Data normalization is a process used in database management to organize data in a standardized and efficient manner. It involves structuring a database in such a way that reduces redundancy and dependency by dividing it into multiple related tables. This helps in improving data accuracy, efficiency, and consistency.

Data Normalization Benefits:

1. Data Accuracy: By eliminating duplicate data and inconsistencies, normalization ensures data accuracy.

2. Data Efficiency: It improves data retrieval and processing speed as data is stored more efficiently.

3. Data Integrity: Normalization reduces the chances of data anomalies and ensures data integrity.

Techniques for Data Normalization:

1. First Normal Form (1NF): Ensures that each table has a primary key and that all attributes are atomic.

2. Second Normal Form (2NF): Requires the removal of partial dependencies by creating separate tables for related data.

3. Third Normal Form (3NF): Eliminates transitive dependencies by breaking down tables into smaller, related tables.

By following these normalization techniques, database designers can create well-structured relational databases that are optimized for efficient data organization, processing, and management.