DA0-002 Data Concepts and Environments Practice Question
During an ETL process, a data quality check fails due to duplicate customer IDs. Which data quality dimension is violated?
⚠ Common exam trap
Candidates often confuse uniqueness with accuracy, thinking a duplicate ID is 'inaccurate' data, but accuracy concerns correctness of values, not their distinctness.
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 customer IDs violate the uniqueness dimension because uniqueness ensures that each record in a dataset has a distinct identifier with no duplicates. In an ETL process, a primary key or unique constraint on the customer ID column would reject duplicate values, causing the data quality check to fail. This is distinct from consistency, which checks for logical agreement across data sources.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Consistency
Why it's wrong here
Consistency concerns conflicting values across sources or formats, not repeated identifiers within a dataset. It is tempting because duplicates look like conflicting records, but it would be correct when the same attribute disagrees between systems; uniqueness is the dimension violated by duplicate customer IDs.
- ✓
Uniqueness
Why this is correct
Duplicate customer IDs breach uniqueness, the dimension requiring each real-world entity to appear only once within its dataset. This directly satisfies the stem's constraint: the ETL quality check detected repeated identifiers. Uniqueness differs from accuracy, which concerns correctness of values, and from completeness, which concerns missing values — neither applies to repeated IDs.
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Completeness
Why it's wrong here
Completeness concerns missing values or records, not repeated customer IDs. It is tempting because duplicates feel like missing distinctness, but it would be correct when required fields or rows are absent; uniqueness is the dimension breached by duplicate identifiers.
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Accuracy
Why it's wrong here
Duplicate customer IDs breach uniqueness, not accuracy; accuracy concerns whether a value correctly describes the real-world entity. It tempts because duplicate records often contain stale or conflicting attributes, so accuracy problems frequently accompany them, but the dimension tested here is the one-to-one mapping of each record to a distinct customer.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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