What is normalization's impact on update anomalies?

• A. Normalization makes updates faster by duplicating data.
• B. Normalization eliminates the need for constraints.
• C. Normalization reduces update anomalies by eliminating redundant data, ensuring consistent updates.
• D. Normalization only affects read performance.

Answer: (C)

Normalization reduces data redundancy by organizing data into related tables. When the same fact is stored in multiple places, an update must be performed in all those places; if one copy is updated and another isn’t, the data becomes inconsistent—an update anomaly. By splitting data into related tables and using keys to link them, normalization ensures that a single update changes data in only one place, maintaining consistency across the database. That’s why the impact on update anomalies is that they are minimized by eliminating redundant data, ensuring consistent updates.

The other statements don’t fit: normalization does not speed updates by duplicating data (it actually avoids duplication), it does not eliminate the need for constraints (constraints help maintain integrity and normalization relies on them), and normalization can affect write performance because joining data from multiple tables may be required to perform certain updates.