Which data quality attribute ensures a dataset has no duplicative or redundant records?

Which data quality attribute ensures a dataset has no duplicative or redundant records?

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

Answer: (C)

This item centers on preventing duplicate records in a dataset, which is addressed by ensuring uniqueness. Uniqueness means every record has a distinct identity, typically enforced through a primary key or a unique constraint so that no two rows share the same key. This directly stops duplicative or redundant entries, keeping analytics, joins, and data integrity reliable. Timeliness concerns whether data is current and up-to-date, not whether there are duplicates. Completeness deals with whether all required fields are present, not with duplicates. Accuracy is about the correctness of the data values themselves, which can be correct even if a record is a duplicate.

This item centers on preventing duplicate records in a dataset, which is addressed by ensuring uniqueness. Uniqueness means every record has a distinct identity, typically enforced through a primary key or a unique constraint so that no two rows share the same key. This directly stops duplicative or redundant entries, keeping analytics, joins, and data integrity reliable.

Timeliness concerns whether data is current and up-to-date, not whether there are duplicates. Completeness deals with whether all required fields are present, not with duplicates. Accuracy is about the correctness of the data values themselves, which can be correct even if a record is a duplicate.