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Data Acquisition and PreparationmediumMultiple ChoiceObjective-mapped

DA0-002 Data Acquisition and Preparation Practice Question

An analyst needs to combine two datasets from different sources that share a common key but have different levels of granularity. Dataset A has daily sales per store, Dataset B has hourly foot traffic per store. The analyst wants to analyze correlation. Which approach is appropriate?

⚠ Common exam trap

CompTIA often tests the misconception that disaggregating (splitting) the coarser dataset is acceptable, but this introduces artificial data and violates the assumption of uniform distribution, whereas aggregation preserves the actual measured values.

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

Aggregate Dataset B to daily level before merging

Aggregating Dataset B (hourly foot traffic) to the daily level ensures both datasets share the same granularity before merging on the common key (store and date). This allows a valid correlation analysis between daily sales and daily foot traffic without introducing artificial patterns or data duplication. Merging at mismatched granularities would violate the assumption that each row represents a comparable unit of observation.

Answer analysis

Option-by-option breakdown

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

  • Aggregate Dataset B to daily level before merging

    Why this is correct

    Aggregating the more granular dataset to match the less granular is the standard approach.

  • Use an outer join and keep all rows

    Why it's wrong here

    Outer join still has granularity mismatch and may produce nulls.

  • Disaggregate Dataset A to hourly level by dividing daily sales by hours

    Why it's wrong here

    Disaggregating assumes uniform distribution, which may not be accurate.

  • Join on store and date without aggregation

    Why it's wrong here

    Joining without aggregation causes one-to-many relationships and duplicates.

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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.