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Data Concepts and EnvironmentseasyMultiple ChoiceObjective-mapped

DA0-002 Data Concepts and Environments Practice Question

Exhibit

ID, Name, Salary, Department
1, Alice, 60000, Sales
2, Bob, 70000, IT
3, Charlie, , IT

Refer to the exhibit. Which data quality dimension is compromised by the missing value for Charlie's salary?

⚠ Common exam trap

CompTIA often tests the distinction between 'missing' (completeness) and 'wrong' (accuracy), leading candidates to confuse a null value with an incorrect value.

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

Completeness

Completeness measures whether all required data is present. Charlie's missing salary value means the record is incomplete, directly violating this dimension. In data quality frameworks, completeness is assessed by the proportion of non-null values in a field, and a null salary here fails that check.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Uniqueness

    Why it's wrong here

    Incorrect. Uniqueness concerns duplicate records.

  • Completeness

    Why this is correct

    Correct. The salary field is missing, so data is incomplete.

  • Timeliness

    Why it's wrong here

    Incorrect. Timeliness relates to data being up-to-date.

  • Accuracy

    Why it's wrong here

    Incorrect. Accuracy is about correctness; here data is missing, not incorrect.

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Written by Johnson Ajibi, MSc IT Security

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