DA0-002 Data Governance Practice Question
An analyst is creating a data story about the decline in customer satisfaction scores. The data shows that satisfaction dropped after a software update. Which narrative structure best helps the audience understand the cause and effect?
⚠ Common exam trap
Watch out — candidates often choose Option A because they think starting with the current state is more engaging, but CompTIA Data+ tests the understanding that a chronological cause-and-effect narrative is required to clearly demonstrate the impact of a specific event, not just a general trend.
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
✓
Begin with the software update event, then show satisfaction before and after
It follows a chronological cause-and-effect narrative, starting with the software update event and then showing satisfaction scores before and after. This structure directly maps to the audience's need to understand the causal relationship, as it highlights the intervention point and the resulting change in the metric. In data storytelling, this is known as the 'before-and-after' or 'change-over-time' narrative, which is most effective for demonstrating impact.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Start with the current scores, then show historical trend
Why it's wrong here
Showing current scores then historical trend establishes a timeline but never isolates the software update as the cause, leaving correlation unaddressed. It is tempting because trend narratives suit showing change over time, and would fit a question asking how satisfaction evolved rather than why it dropped.
- ✓
Begin with the software update event, then show satisfaction before and after
Why this is correct
Opening with the software update establishes the causal event, then before-and-after satisfaction figures demonstrate its effect. This chronological cause-then-effect ordering directly satisfies the requirement to make the relationship between the update and the decline understandable.
- ✗
Present all data points without a story
Why it's wrong here
Listing every data point without narrative gives the audience no causal link between the update and the satisfaction drop, so they must infer it themselves. It is tempting because raw data presentation suits exploratory analysis or data-quality review, not explanatory storytelling where a specific cause must be communicated.
- ✗
Use a pie chart of satisfaction categories
Why it's wrong here
A pie chart shows parts of a whole at one moment, so it cannot express the drop's timing relative to the software update. It is tempting because pie charts suit proportional breakdowns, such as satisfaction categories' share of total responses, but cause-and-effect needs a temporal sequence.
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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.