Does proper normalization eliminate duplicated data?

Introduction / Context:
A central goal of normalization is to eliminate unnecessary duplication that leads to anomalies. This does not mean the database contains no repeated values at all (for example, many rows may share the same city), but rather that redundant storage of the same fact across multiple rows or tables is minimized by proper design.

Given Data / Assumptions:

• Redundancy driven by functional or multivalued dependencies is the target of normalization.
• Normal forms (1NF through BCNF/4NF/5NF) progressively remove types of redundancy.
• Some environments intentionally denormalize for performance, accepting controlled redundancy.

Concept / Approach:
By ensuring that every determinant is a key (BCNF) and separating independent multi-valued attributes (4NF), a design stops storing the same fact in multiple places. As a result, updates are localized, and consistency improves. While some repetition of domain values remains natural (for example, many customers may have state = CA), that repetition is not problematic because it does not represent duplicated facts.

Step-by-Step Solution:

Verification / Alternative check:
Compare update paths pre/post normalization: changing a department’s name affects 1 row in DEPARTMENT rather than hundreds in EMPLOYEE, proving duplication removal.

Why Other Options Are Wrong:

• Claiming normalization increases duplication confuses logical design with physical storage overhead (for example, additional keys).
• Surrogate keys, storage engines, or read-only status do not change the logical principle.

Common Pitfalls:
Equating repeating domain values with duplication of facts; assuming denormalization is always better for performance; neglecting constraints that enforce the intended design.

Final Answer:
Valid (proper normalization removes unnecessary duplication caused by dependencies)