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Data Acquisition and PreparationmediumMultiple SelectObjective-mapped

DA0-002 Data Acquisition and Preparation Practice Question

Which THREE are best practices for data profiling during acquisition? (Choose three.)

⚠ Common exam trap

Watch out — candidates often confuse 'best practices for acquisition' with 'best practices for transformation,' leading them to select normalization (Option A) as an immediate step rather than a later processing stage.

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

Check for completeness

Checking for completeness (Option B) is a best practice during data acquisition because it ensures that all required fields and records are present before further processing. Incomplete data can lead to incorrect analysis or failed transformations, so profiling for missing values or nulls is a fundamental validation step.

Answer analysis

Option-by-option breakdown

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

  • Immediately normalize data

    Why it's wrong here

    Normalization should occur after profiling, not during.

  • Check for completeness

    Why this is correct

    Ensuring all required fields are populated is essential.

  • Assess data types

    Why this is correct

    Verifying data types helps prevent integration errors.

  • Identify outliers

    Why this is correct

    Outliers can indicate data quality issues.

  • Skip validation for trusted sources

    Why it's wrong here

    Even trusted sources can have issues; validation is always needed.

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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.