This DA0-001 practice question tests your understanding of comparing and contrasting data concepts. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
During an ETL process, a data quality check fails due to duplicate customer IDs. Which data quality dimension is violated?
Consistency
Why wrong: Consistency is about uniform representation, not duplicates.
Uniqueness
Duplicates violate the uniqueness dimension.
Completeness
Why wrong: Completeness is about missing data, not duplicates.
Accuracy
Why wrong: Accuracy concerns correctness of values, not duplicates.
Answer choices
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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
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 is about uniform representation, not duplicates.
Uniqueness
Why this is correct
Duplicates violate the uniqueness dimension.
Related concept
Read the scenario before looking for a memorised answer.
Completeness
Why it's wrong here
Completeness is about missing data, not duplicates.
Accuracy
Why it's wrong here
Accuracy concerns correctness of values, not duplicates.
Common exam traps
The trap here is that candidates confuse uniqueness with accuracy, thinking a duplicate ID is 'inaccurate' data, but accuracy concerns correctness of values, not their distinctness.
Detailed technical explanation
Uniqueness is enforced in databases via primary key constraints or unique indexes, which prevent duplicate entries at the storage engine level. In ETL pipelines, a duplicate check often involves a hash-based deduplication step or a SQL COUNT(*) > 1 query on the target column. A real-world scenario is a CRM system where duplicate customer IDs cause merge conflicts, leading to incorrect sales reporting and broken foreign key relationships.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A practitioner preparing for the DA0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Comparing and Contrasting Data Concepts — This question tests Comparing and Contrasting Data Concepts — Read the scenario before looking for a memorised answer..
The correct answer is: 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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
This DA0-001 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 DA0-001 exam.
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