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

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

• A. Normalization reduces data redundancy and improves data integrity by organizing data into related tables.
• B. Normalization increases data redundancy.
• C. Normalization stores data in a single table only.
• D. Normalization is primarily about improving query performance by denormalization.

Answer: (A)

Normalization is a design process in relational databases that organizes data into related tables to minimize duplication. By splitting data into logical, connected tables and using keys to link them, updates, deletions, and insertions occur in one place, which prevents anomalies and inconsistencies that come from having the same data stored in many places. This improves data integrity and makes maintenance easier, because a change to a single fact is reflected everywhere without needing multiple updates. For example, storing a customer’s address in a separate customers table and linking it to orders via a customer ID avoids duplicating the address in every order record. The other statements miss the essence: they describe increasing redundancy, storing everything in one table, or focusing on performance via denormalization, which is not what normalization aims for.

Normalization is a design process in relational databases that organizes data into related tables to minimize duplication. By splitting data into logical, connected tables and using keys to link them, updates, deletions, and insertions occur in one place, which prevents anomalies and inconsistencies that come from having the same data stored in many places. This improves data integrity and makes maintenance easier, because a change to a single fact is reflected everywhere without needing multiple updates. For example, storing a customer’s address in a separate customers table and linking it to orders via a customer ID avoids duplicating the address in every order record. The other statements miss the essence: they describe increasing redundancy, storing everything in one table, or focusing on performance via denormalization, which is not what normalization aims for.