Normalization reduces data redundancy by doing what?

Normalization reduces data redundancy by doing what?

• A. Storing all data in a single table
• B. Organizing data into related tables
• C. Increasing data duplication
• D. Eliminating constraints

Answer: (B)

Normalization reduces data redundancy by organizing data into related tables, each representing a distinct type of entity, and linking them with keys. This separation means you store each piece of information in one place, so updates, deletions, and inserts don’t have to be repeated across many rows. For example, instead of duplicating student details in every course enrollment record, you keep student data in a separate table and reference it from enrollments via a foreign key. The use of primary and foreign keys enforces data integrity across the related tables. So the clean, related-table structure minimizes repetition and makes updates safer and more efficient. The other ideas—putting everything in one big table, increasing duplication, or removing constraints—would undermine that benefit.

Normalization reduces data redundancy by organizing data into related tables, each representing a distinct type of entity, and linking them with keys. This separation means you store each piece of information in one place, so updates, deletions, and inserts don’t have to be repeated across many rows. For example, instead of duplicating student details in every course enrollment record, you keep student data in a separate table and reference it from enrollments via a foreign key. The use of primary and foreign keys enforces data integrity across the related tables. So the clean, related-table structure minimizes repetition and makes updates safer and more efficient. The other ideas—putting everything in one big table, increasing duplication, or removing constraints—would undermine that benefit.