The correct approach is to acknowledge the discrepancy and explain possible reasons such as changes in data collection methods or patient population. This choice directly addresses the core challenge of communicating findings to skeptical stakeholders by validating their concerns rather than dismissing them, which preserves the analyst’s credibility. On the CompTIA Data+ DA0-001 exam, this scenario tests the competency of “Communicating Data Insights,” specifically how to handle pushback by inviting collaborative investigation into data quality issues. A common trap is choosing an option that defends the data without acknowledging the conflict, which erodes trust. Instead, remember the “Acknowledge-Explain-Invite” framework: first validate the discrepancy, then offer plausible causes, and finally propose joint verification. A useful memory tip is “Skeptics need a bridge, not a wall”—build trust by meeting their skepticism with transparency.
DA0-001 Communicating Data Insights Practice Question
This DA0-001 practice question tests your understanding of communicating data insights. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 healthcare data analyst is presenting findings on patient readmission rates to a group of hospital administrators. The analysis reveals a 15% increase in readmissions over the past quarter for patients aged 65+ from a specific zip code. However, the administrators are skeptical because previous quarterly reports showed no such trend, and they suspect data quality issues. The analyst must communicate this insight effectively while maintaining credibility. Which of the following approaches should the analyst take?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Acknowledge the discrepancy and explain possible reasons such as changes in data collection methods or patient population
Option D is correct because it demonstrates the core competency of 'Communicating Data Insights' by acknowledging the discrepancy between the current finding and previous reports, which builds trust with skeptical stakeholders. By explaining possible reasons such as changes in data collection methods or patient population, the analyst maintains credibility and invites collaborative investigation into data quality issues, rather than dismissing concerns or hiding details.
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.
✗
Emphasize the statistical significance of the finding and ignore previous reports
Why it's wrong here
Ignoring previous reports undermines credibility and does not address the audience's concerns.
✗
Present the data without any explanation and let them draw conclusions
Why it's wrong here
Without explanation, the audience may dismiss the finding due to the discrepancy.
✗
Remove the demographic detail to avoid controversy
Why it's wrong here
Removing details hides important insights and could be seen as dishonest.
✓
Acknowledge the discrepancy and explain possible reasons such as changes in data collection methods or patient population
Why this is correct
This approach maintains trust and provides context, making the insight more believable.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may choose Option A, thinking statistical significance alone validates the finding, but the DA0-001 exam emphasizes that effective communication requires acknowledging and addressing stakeholder concerns about data quality, not just presenting numbers.
Detailed technical explanation
How to think about this question
In healthcare analytics, data quality issues such as changes in ICD-10 coding practices, shifts in patient enrollment periods, or modifications to the electronic health record (EHR) system can introduce artifacts that mimic real trends. A robust approach involves performing a sensitivity analysis—comparing the current quarter's data against historical baselines while controlling for variables like seasonality or payer mix—to isolate whether the 15% increase is a true signal or a data artifact. Real-world scenarios often require the analyst to present a 'data quality scorecard' alongside findings to preemptively address stakeholder skepticism.
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 small business has 20 workstations on the 192.168.1.0/24 network and one public IP from its ISP. The router uses PAT (NAT overload) so all 20 devices share one public address using different source ports. NAT questions test whether you understand the four address terms and which direction each translation applies.
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: Acknowledge the discrepancy and explain possible reasons such as changes in data collection methods or patient population — Option D is correct because it demonstrates the core competency of 'Communicating Data Insights' by acknowledging the discrepancy between the current finding and previous reports, which builds trust with skeptical stakeholders. By explaining possible reasons such as changes in data collection methods or patient population, the analyst maintains credibility and invites collaborative investigation into data quality issues, rather than dismissing concerns or hiding details.
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.
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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