DA0-002 Data Concepts and Environments Practice Question
A data quality report shows that 95% of records have all required fields completed, but 20% of the completed fields contain values that are outside valid ranges. Which data quality dimension is most affected?
⚠ Common exam trap
The trap here is that candidates see '95% of records have all required fields completed' and immediately think 'Completeness is high, so that dimension is fine,' but then incorrectly assume the 20% out-of-range values also affect Completeness, when in fact Accuracy is the dimension that suffers when present data is invalid.
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 measures how well data reflects real-world values or a defined standard. Here, 20% of completed fields contain values outside valid ranges, meaning the data is present but incorrect, directly degrading accuracy. Completeness (95% filled) is high, but the core issue is that the values themselves are wrong, not missing or late.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Consistency
Why it's wrong here
Consistency measures whether the same value agrees across systems or records, not whether a value falls inside a permitted range. The stem describes values outside valid ranges, which is validity. Consistency would be the correct dimension if, for example, a customer's address differed between the CRM and the billing platform.
- ✓
Accuracy
Why this is correct
Accuracy measures whether values correctly represent reality and fall within valid domains. Completeness is already high at 95%, but out-of-range values breach validity and correctness, so accuracy is the dimension most affected by this defect.
- ✗
Timeliness
Why it's wrong here
Timeliness measures whether data is current and available when needed, so it cannot describe values falling outside permitted ranges. It is tempting because late-arriving records can indeed undermine a quality report, and timeliness would be the correct dimension if the stem described stale or delayed data rather than out-of-range values.
- ✗
Completeness
Why it's wrong here
Completeness measures missing values, and 95% of records already have every required field populated, so it does not address the 20% of completed fields holding out-of-range values — that is validity. Completeness would be the answer if records were missing required fields entirely, such as null customer IDs.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DA0-002 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DA0-002 exam.