What is a potential drawback of denormalization when consolidating data into a single table?

• A. It improves data integrity
• B. It reduces storage usage
• C. It guarantees no anomalies
• D. It may introduce duplicate data

Answer: (D)

Denormalization trades data integrity for speed by duplicating data to reduce the need for joins when querying. When you consolidate data into a single table, you often reuse the same information in multiple places, so the same piece of data ends up stored more than once. This duplication is the core reason it can cause problems: any change to that data must be applied to every copy, and if one copy isn’t updated consistently, you end up with inconsistent or stale information. That’s why a potential drawback is that duplicates may be introduced.

Since duplicates exist, storage usage tends to grow, and update anomalies can appear because changes must be propagated across all copies. The other statements describe outcomes that aren’t guaranteed with denormalization: it doesn’t inherently improve data integrity, and it doesn’t reduce storage usage; it can actually increase it, and it doesn’t guarantee no anomalies.