DA0-002 Data Analysis Practice Question
Which TWO of the following data quality dimensions are most directly affected by duplicate records?
⚠ Common exam trap
The trap is assuming that duplicates only affect uniqueness, but they also impact accuracy because the data no longer correctly represents the real-world entity.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Uniqueness
Duplicate records most directly undermine Uniqueness (C), because uniqueness is the data quality dimension that measures whether each real-world entity appears exactly once in a dataset; duplicates violate this one-record-per-entity rule by definition. They also directly affect Accuracy (D), since duplicated rows distort counts, aggregations, and the true representation of the entity, making the stored data an incorrect reflection of reality. Timeliness (A) concerns whether data is current and available when needed, which duplicates do not inherently affect. Consistency (B) refers to agreement of the same data across systems or formats, which is a separate issue from repeated rows. Completeness (E) measures whether required data is present, and duplicates add data rather than omit it, so it is not the dimension most directly impacted.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Timeliness
Why it's wrong here
Timeliness measures whether data reflects the current state at the required moment; duplicate rows can be equally current, so this dimension is untouched. It is tempting because stale source extracts frequently introduce duplicates, yet the dimension duplicates directly breach is uniqueness, not currency.
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Consistency
Why it's wrong here
Duplicate records breach uniqueness, not consistency, which concerns whether values conform to the same format, units or rules across systems and records. Consistency is tempting because duplicates often accompany inconsistent formatting, but the dimension directly measured by duplicate detection is uniqueness.
- ✓
Uniqueness
Why this is correct
Duplicate records mean the same real-world entity appears more than once, directly violating the uniqueness dimension, which measures whether each record occurs only once. This is the dimension most immediately degraded by duplication, independent of whether the underlying values are otherwise correct.
- ✓
Accuracy
Why this is correct
Duplicates distort counts, sums and aggregates, so derived figures no longer reflect reality, degrading accuracy. Because accuracy measures how correctly data represents the events it describes, repeated rows corrupt that representation, making it the second dimension directly affected by duplicate records.
- ✗
Completeness
Why it's wrong here
Duplicates inflate row counts rather than remove required values, so completeness — the presence of all required attributes — remains unaffected. Completeness is tempting because deduplication projects often clean missing values alongside duplicates, but the dimension duplicates directly violate is uniqueness.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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