DA0-002 Data Governance Practice Question
A government agency's data analyst is commissioned to produce a report on public transportation usage trends. The report will be read by policymakers, transit planners, and the general public. The data includes ridership numbers, delay rates, and demographic breakdowns. The analyst needs to ensure the report is accessible and persuasive, especially to non-technical readers. The goal is to advocate for increased funding in underserved areas. The report must be data-driven but also tell a compelling story. What strategy should the analyst prioritize?
⚠ Common exam trap
Test-takers frequently choose Option C (complex statistical analysis) because they equate 'data-driven' with technical rigor, failing to recognize that the exam's focus on 'communicating data insights' prioritizes accessibility and persuasion over statistical complexity for non-technical stakeholders.
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
✓
Create a narrative that highlights the impact of delayed trains on low-income commuters.
It directly addresses the need to make data accessible and persuasive to non-technical readers by weaving a narrative around a specific, relatable impact (delayed trains on low-income commuters). This approach aligns with the goal of advocating for increased funding in underserved areas, as it humanizes the data and creates a compelling story that policymakers and the public can understand and act upon, without requiring technical expertise.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Provide raw data in appendices only.
Why it's wrong here
No narrative; data alone is not persuasive without interpretation.
- ✓
Create a narrative that highlights the impact of delayed trains on low-income commuters.
Why this is correct
Makes data relatable and persuasive, driving home the need for funding.
- ✗
Use complex statistical analysis to show significance of trends.
Why it's wrong here
May confuse non-technical readers and reduce accessibility.
- ✗
Focus solely on ridership numbers without context.
Why it's wrong here
Lacks context and fails to engage readers emotionally.
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