If the same piece of data is stored in two different places in a database system, what are the primary consequences for storage and consistency management?

Introduction / Context:
Data redundancy occurs when the same fact is stored multiple times. Although sometimes deliberate (caching or denormalization), redundancy generally increases costs and risks. Understanding the trade-offs helps designers decide when normalization should be enforced and when controlled redundancy is acceptable.

Given Data / Assumptions:

• A single logical fact is stored in two locations (tables or columns).
• There is no strict mechanism ensuring both copies are updated together.
• We are concerned with storage efficiency and data integrity.

Concept / Approach:
Redundant storage wastes space, especially at scale. More importantly, it introduces the chance of inconsistency: one copy might be updated while the other is not, producing conflicting answers depending on the query path. Normal forms in relational theory aim to reduce such redundancy by placing each fact in a single, authoritative location and using keys to relate data without repetition.

Step-by-Step Solution:

Verification / Alternative check:
Texts on database normalization list update, insert, and delete anomalies as direct consequences of redundancy, validating the choice.

Why Other Options Are Wrong:

• Only (a): ignores integrity problems.
• Only (b): ignores capacity and cost impacts.
• “More easily accessed”: not guaranteed; duplication can complicate queries.
• None: the risks are real and well documented.

Common Pitfalls:
Using redundancy as a shortcut for performance without implementing constraints, triggers, or application logic to keep copies synchronized.

Final Answer:
both (a) and (b)