What is data normalization in relational databases and why is it used?

What is data normalization in relational databases and why is it used?

• A. Storing data in a single large table.
• B. Structuring data to reduce redundancy and improve integrity by separating data into related tables.
• C. Encrypting data fields to enhance security.
• D. Increasing redundancy to improve retrieval speed.

Answer: (B)

Data normalization is organizing data in a relational database to minimize duplication and keep data consistent. It does this by breaking data into multiple related tables and using keys to connect them, rather than putting everything into one big table. This reduction of redundancy means when something changes, you update it in one place, which prevents inconsistencies and anomalies during inserts, updates, and deletes. Normalization often follows steps (normal forms) that enforce dependencies so that attributes rely on the right keys and not on each other, supporting data integrity and flexible, scalable schemas. The description matches structuring data to reduce redundancy and improve integrity by separating data into related tables. The other options miss the core idea: storing all data in a single table creates redundancy; encryption is about security, not structure; increasing redundancy harms integrity and performance.

Data normalization is organizing data in a relational database to minimize duplication and keep data consistent. It does this by breaking data into multiple related tables and using keys to connect them, rather than putting everything into one big table. This reduction of redundancy means when something changes, you update it in one place, which prevents inconsistencies and anomalies during inserts, updates, and deletes. Normalization often follows steps (normal forms) that enforce dependencies so that attributes rely on the right keys and not on each other, supporting data integrity and flexible, scalable schemas. The description matches structuring data to reduce redundancy and improve integrity by separating data into related tables. The other options miss the core idea: storing all data in a single table creates redundancy; encryption is about security, not structure; increasing redundancy harms integrity and performance.