DA0-002 Data Concepts and Environments Practice Question
A data governance team is establishing policies for data quality. Which THREE of the following are common dimensions of data quality? (Select 3)
⚠ Common exam trap
A common mix-up: candidates confuse the characteristics of big data (velocity, volume, variety) with the dimensions of data quality, leading them to select velocity or volume instead of the correct quality-focused options.
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
✓
Consistency
Consistency is a common dimension of data quality because it ensures that data values are uniform across different datasets or systems, preventing contradictions. For example, if a customer's address is stored as '123 Main St' in one database and '123 Main Street' in another, consistency rules would flag this discrepancy. This dimension is critical for reliable reporting and integration.
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 this is correct
Data is uniform across systems.
- ✓
Completeness
Why this is correct
All required data is present.
- ✓
Accuracy
Why this is correct
Data correctly reflects real-world values.
- ✗
Velocity
Why it's wrong here
Velocity is a characteristic of big data, not quality.
- ✗
Volume
Why it's wrong here
Volume is a quantity measure, not a quality dimension.
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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.