DA0-002 Data Governance Practice Question
A retail company has a data warehouse that integrates sales data from multiple sources including online transactions, in-store POS, and third-party marketplaces. The data team recently updated the ETL pipeline to add a new data source: mobile app purchases. After the update, the daily sales report shows a 15% increase in total sales compared to the previous day, which is unexpected because the mobile app is new and only contributed 2% of sales in tests. The report is created by a SQL script that aggregates sales by date and runs every morning. The data team needs to identify the cause of the discrepancy. Which of the following should the team do first?
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
✓
Verify that the date filter in the SQL script is correct and not including future dates.
The correct first step because an unexpected 15% increase in total sales, especially when the new mobile app source accounts for only 2% in tests, suggests a data integrity issue rather than a real sales surge. The most common cause is a date filter error in the SQL script, such as including future dates or applying an incorrect date range, which would inflate the daily total. Verifying the date filter is a quick, low-effort check that can confirm the data source before investigating more complex issues like double-counting (Option D). Options B and C are premature: comparing raw transaction counts is a secondary step after confirming the date filter, and assuming the increase is real (C) ignores the most likely data problem.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Verify that the date filter in the SQL script is correct and not including future dates.
Why this is correct
Correct. A date filter error is a common cause of sudden large increases and should be checked first.
- ✗
Compare the raw transaction counts from each source for that day.
Why it's wrong here
Incorrect. This is a good step but may not catch the most common issue first.
- ✗
Assume the increase is due to the mobile app and update the forecast.
Why it's wrong here
Incorrect. This assumption could be wrong and leads to inaccurate forecasting.
- ✗
Check if the ETL pipeline is double-counting transactions from the mobile app source.
Why it's wrong here
Incorrect. Double-counting is possible but less likely than a date filter issue.
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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.