Which data quality dimension ensures there are no duplicate records?

• A. Accuracy
• B. Completeness
• C. Validity
• D. Uniqueness

Answer: (D)

This question focuses on ensuring that each record appears only once in a dataset. That property is Uniqueness, which means no two records share the same identifying value or key. When a dataset enforces uniqueness—often through a primary key or a unique constraint—it prevents duplicates, preserving accurate counts and reliable relationships between records. Duplicates can skew analytics, inflate totals, and distort business insights, so maintaining uniqueness keeps the data representation clean and trustworthy.

Other dimensions address different aspects: Accuracy checks whether the data values are correct; Completeness ensures required fields are present; Validity ensures values conform to defined formats or domains. While all are important, they do not specifically target the presence of duplicate records, making Uniqueness the best fit for this scenario.