A transit authority CRM lists the same rider under three slightly different names and phone formats. What data quality problem does this primarily represent?
Select an answer to reveal the explanation.
Short Explanation
Three 'different' riders who are really one person is like three library cards for the same borrower—operations get messy fast. Uniqueness fails when duplicates of the same entity pile up. Slight name and phone format drift is a classic duplicate-entity risk.
Full Explanation
Uniqueness requires that each real-world entity is represented once as intended. Multiple near-duplicate rider records degrade trust, analytics, and service operations. Format variation often contributes to failed matching, but the core DQ dimension at issue is uniqueness of the entity.