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Data Concepts and EnvironmentsmediumMultiple ChoiceObjective-mapped

DA0-002 Data Concepts and Environments Practice Question

A data analyst is working with a dataset that contains customer names and addresses. Some records have missing state codes. Which data quality issue is this?

⚠ Common exam trap

A common mix-up: candidates confuse incompleteness with inconsistency, but incompleteness is about missing data (nulls), while inconsistency is about contradictory data across records.

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

Incompleteness

Incompleteness is the correct answer because missing state codes in customer address records represent a lack of required data. This is a classic example of incomplete data, where fields that should contain values are left null or blank, reducing the dataset's usability for analysis.

Answer analysis

Option-by-option breakdown

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

  • Duplication

    Why it's wrong here

    Duplication is about repeated records, not missing data.

  • Incompleteness

    Why this is correct

    Missing state codes make the record incomplete.

  • Outliers

    Why it's wrong here

    Outliers are extreme values, not missing data.

  • Inconsistency

    Why it's wrong here

    Inconsistency refers to contradictory data, not missing values.

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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.