DA0-002 Data Acquisition and Preparation Practice Question
You are analyzing sales data and need to calculate the moving average of monthly sales over the previous 3 months for each month. Which type of function is best suited for this task?
⚠ Common exam trap
The trap is choosing GROUP BY because 'average' sounds like an aggregate — but GROUP BY collapses rows, whereas a moving average requires per-row output, which only window functions provide.
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
✓
Window function with OVER()
A window function with OVER() computes a value across a defined set of rows related to the current row without collapsing them, which is exactly what a moving average over the previous 3 months requires. The OVER() clause defines the window (e.g., ROWS BETWEEN 2 PRECEDING AND CURRENT ROW), and the aggregate (AVG) is applied per row while preserving all rows.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
String function
Why it's wrong here
String functions manipulate text characters, so they cannot compute a rolling mean across numeric sales rows. They are tempting because month labels are text, but the calculation needs a windowed aggregate over ordered rows, not concatenation or substring operations.
- ✓
Window function with OVER()
Why this is correct
A window function with OVER() computes an aggregate across a defined frame of preceding rows while retaining each row's detail. This satisfies the three-month moving average requirement, which GROUP BY cannot produce without collapsing the monthly rows.
- ✗
Aggregate function with GROUP BY
Why it's wrong here
GROUP BY collapses each month into one aggregated row, destroying the per-month detail a three-month moving window requires. It is tempting because it does aggregate sales, but it is correct for totals per category, not for sliding windows across consecutive periods.
- ✗
Date function
Why it's wrong here
Date functions extract or manipulate date components such as month or year; they do not compute a rolling three-month average across ordered rows. They are tempting because the data is monthly, but the task needs a window function with a ROWS BETWEEN frame.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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.