DA0-002 Data Governance Practice Question
A data analyst is troubleshooting a dashboard that displays slowly. Which two of the following are common causes of dashboard performance issues? (Select TWO.)
⚠ Common exam trap
Candidates often confuse 'summary tables' (which improve performance) with 'large unaggregated datasets' (which degrade it), and they may overlook that complex calculated fields with dependencies are a hidden performance killer.
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
✓
Large unaggregated datasets.
Large unaggregated datasets force the dashboard to process every row of raw data at query time, which dramatically increases load times and memory consumption. Aggregated or pre-summarized tables reduce the volume of data scanned, improving performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Minimal use of filters.
Why it's wrong here
Incorrect. Few filters reduce query complexity, improving performance.
- ✗
Use of summary tables.
Why it's wrong here
Incorrect. Summary tables pre-aggregate data and improve performance.
- ✓
Large unaggregated datasets.
Why this is correct
Correct. Large unaggregated datasets increase load on the dashboard.
- ✓
Complex calculated fields with many dependencies.
Why this is correct
Correct. Complex calculations can slow down rendering.
- ✗
Excessive use of live data connections.
Why it's wrong here
Incorrect. Live connections can be performant if properly designed; not inherently a cause of slowness.
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