The correct answer is to normalize the sales data by region and explain the data anomaly in the report. This is the best practice because the steep drop in monthly sales was caused by adding a new region mid-month without normalizing the data, which artificially diluted the overall figure. Normalizing by region—such as calculating sales per region or as a percentage of total—removes the distortion, while explicitly explaining the anomaly ensures transparency and data integrity. On the CompTIA Data+ DA0-001 exam, this scenario tests your ability to communicate data insights accurately, a key domain where examiners often set traps by presenting options like ignoring the anomaly or simply adjusting the chart without explanation. A common memory tip is “Normalize to equalize, annotate to communicate”—always adjust for scale differences and then document the reason for any unusual patterns.
DA0-001 Communicating Data Insights Practice Question
This DA0-001 practice question tests your understanding of communicating data insights. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data analyst notices that a line chart showing monthly sales over the past two years has a steep drop in one month. Upon investigation, the analyst discovers that a new sales region was added mid-month and the data was not normalized. Which of the following best practices should the analyst apply to communicate this insight accurately?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Normalize the sales data by region and explain the data anomaly in the report.
Option C is correct because the core issue is that the sales data is not normalized by region, causing a misleading drop when a new region was added mid-month. By normalizing the data (e.g., calculating per-region averages or percentages) and explicitly noting the anomaly in the report, the analyst ensures accurate communication of insights. This aligns with the DA0-001 domain of Communicating Data Insights, where transparency and data integrity are paramount.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Remove the month with the drop from the report.
Why it's wrong here
Removing data without explanation hides important context.
✗
Use a bar chart instead to show the data.
Why it's wrong here
Changing chart type does not address the normalization issue.
✓
Normalize the sales data by region and explain the data anomaly in the report.
Why this is correct
Normalization corrects the artifact, and explanation provides transparency.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Present the data as-is and let stakeholders interpret the drop.
Why it's wrong here
This would mislead stakeholders because the drop is due to unnormalized data.
Common exam traps
Common exam trap: answer the scenario, not the keyword
CompTIA often tests the misconception that simply changing the chart type (Option B) or omitting problematic data (Option A) is acceptable, when the correct approach is to normalize and explain the anomaly to maintain data integrity and clarity.
Detailed technical explanation
How to think about this question
Normalization in this context typically involves dividing sales figures by the number of regions or using a per-region metric (e.g., average sales per region) to remove the effect of adding or removing regions. A subtle behavior is that if the new region had significantly lower sales, the drop could be even more pronounced, masking true performance trends. In real-world scenarios, such as quarterly earnings reports, failing to normalize for new acquisitions or divestitures can lead to misleading year-over-year comparisons.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the DA0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Communicating Data Insights — This question tests Communicating Data Insights — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Normalize the sales data by region and explain the data anomaly in the report. — Option C is correct because the core issue is that the sales data is not normalized by region, causing a misleading drop when a new region was added mid-month. By normalizing the data (e.g., calculating per-region averages or percentages) and explicitly noting the anomaly in the report, the analyst ensures accurate communication of insights. This aligns with the DA0-001 domain of Communicating Data Insights, where transparency and data integrity are paramount.
What should I do if I get this DA0-001 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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