DA0-002 Data Analysis Practice Question
Which data quality dimension ensures that data represents the real-world object or event correctly?
⚠ Common exam trap
Test-takers frequently confuse accuracy with completeness or consistency — candidates often pick completeness because the data 'looks full,' but the question asks specifically about correctly representing the real-world object or event.
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
✓
Accuracy
Accuracy is the data quality dimension that measures how closely data values reflect the real-world object, event, or condition they are intended to describe. If a customer's address, a transaction amount, or a sensor reading is recorded incorrectly, the data is inaccurate even if it is complete, consistent, and timely. Accuracy is therefore the dimension specifically concerned with correctness of representation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Accuracy
Why this is correct
Accuracy verifies that values faithfully reflect the real-world object or event they describe, directly satisfying the stem's requirement for correct representation. Unlike validity, which only confirms conformance to defined formats or rules, accuracy measures correspondence with reality itself, making it the dimension that ensures data genuinely depicts what it claims to represent.
- ✗
Completeness
Why it's wrong here
Completeness checks that all required values are present, not that present values are true. It tempts because missing fields can make a record fail to represent its object, so completeness is correct when the requirement is absence of nulls or gaps rather than correctness of the values recorded.
- ✗
Consistency
Why it's wrong here
Consistency checks that values agree across systems, formats and records, not that they match the real world. It tempts because conflicting duplicates can misrepresent an object, so consistency is correct when the requirement is agreement between datasets or across time rather than faithful representation.
- ✗
Timeliness
Why it's wrong here
Timeliness measures whether data is current and available when needed, not whether values match reality. It is tempting because stale records often misrepresent an object's present state, so timeliness is the correct dimension when the requirement concerns data freshness or latency rather than accuracy of representation.
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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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