Design quality check: Do well-structured (properly normalized) relations encourage data anomalies such as insert, update, and delete anomalies? Judge the correctness of this statement.

Introduction / Context:
One of the main goals of relational design is to minimize modification anomalies. Insert, update, and delete anomalies inflate maintenance costs and introduce subtle data quality issues. This question assesses whether proper normalization and relational structuring reduce or, instead, promote such anomalies.

Given Data / Assumptions:

• “Well-structured” means the schema follows accepted normalization principles (at least to 3NF or BCNF where appropriate).
• We consider anomalies caused by redundancy and dependency violations.
• We assume enforcement of keys and referential integrity.

Concept / Approach:
Normalization decomposes wide, redundant tables into smaller relations based on functional dependencies. This reduces duplication of facts and thus minimizes the risk that the same fact must be updated in multiple places. Fewer duplicated facts means fewer opportunities for inconsistencies, which directly reduces anomalies. Therefore, the claim that well-structured relations “encourage” anomalies is the opposite of reality.

Step-by-Step Solution:

Verification / Alternative check:
Try the classic “Student–Course–Instructor” single-table design and observe anomalies. After decomposition into Student, Course, Instructor, and Enrollment tables with keys and FKs, the anomalies disappear or are greatly reduced.

Why Other Options Are Wrong:

• Correct: Would contradict the purpose of normalization.
• Warehouse, surrogate key, or index strategy alone does not reverse the fundamental effect of normalization on anomalies.

Common Pitfalls:
Believing that more tables always increase complexity and therefore anomalies; in reality, more but properly linked tables reduce redundancy and inconsistency.

Final Answer:
Incorrect