Data Normalization

Denormalization

Denormalization is a database optimization technique that involves adding redundant data or grouping data to improve read performance. By incorporating redundant data, the need for joining tables is reduced, resulting in faster query execution.

Normal Forms

First Normal Form (1NF)

First Normal Form (1NF) is the foundational step in the normalization process. It mandates that a table must have a primary key and ensures that all fields are atomic, meaning they hold indivisible values and do not allow null values. Adhering to 1NF helps in eliminating duplicate data and enhances data organization.

Second Normal Form (2NF)

Second Normal Form (2NF) extends the principles of 1NF by ensuring that all non-prime attributes are functionally dependent on the entire candidate key. By achieving 2NF, data redundancy is further reduced as it eliminates dependencies on partial candidate keys, leading to a more streamlined database structure.

Third Normal Form (3NF)

Third Normal Form (3NF) elevates normalization by necessitating that all non-prime attributes are directly dependent on every candidate key. By attaining 3NF, data redundancy and anomalies within the database are significantly minimized, thereby enhancing data integrity and consistency.

Anomalies in Database

Normalization plays a vital role in mitigating various anomalies that can occur in a database, including:

• Update Anomaly: This anomaly arises when modifications made to data in one table are not reflected in the corresponding foreign key in another table, resulting in data inconsistencies.
• Insertion Anomaly: Occurs when new data cannot be added due to dependencies on non-key attributes. Normalization addresses this issue by breaking down tables into smaller, related entities, enabling smoother data insertion.
• Deletion Anomaly: This anomaly occurs when deleting data leads to unintended loss of information. Proper normalization helps in preventing deletion anomalies by structuring data logically and reducing dependencies between tables.