DA0-002 Visualization and Reporting Practice Question
An IT operations team monitors 200 servers. Each server reports CPU utilization (0-100%) every five minutes for the past year. The team wants to visualize the data to identify servers that are consistently over 80% utilization and detect any unusual spikes. They have a large dataset with 100,000+ records per server. The current visualization is a single scatter plot with CPU utilization on the y-axis, time on the x-axis, and each server as a different colored point. The chart is extremely cluttered, with points overlapping and colors indistinguishable. What should the team do to improve the visualization?
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
✓
Use a heatmap showing CPU utilization over time per server, or create small multiple charts (one per server)
Heatmaps and small multiples (trellis charts) are effective for visualizing large, dense datasets with multiple categories. A heatmap can show CPU utilization intensity over time for all servers in a compact form, making it easy to identify consistently high utilization and spikes. Small multiples create separate charts per server, avoiding overlap and allowing comparison. Option B is wrong because a single line chart with 200 lines would be even more cluttered than the scatter plot, making it impossible to distinguish individual servers. Option C is wrong because trend lines remove the individual data points needed to detect unusual spikes, and they would not show the actual utilization values. Option D is wrong because increasing the size of data points would worsen the overlap and clutter, making the chart even less readable.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use a heatmap showing CPU utilization over time per server, or create small multiple charts (one per server)
Why this is correct
Heatmaps compactly show high-density data; small multiples allow per-server trend analysis without overlapping.
- ✗
Switch to a line chart with each server as a separate line
Why it's wrong here
200 lines on one chart are unreadable and overlapping.
- ✗
Add a trend line to each server's data and remove the individual points
Why it's wrong here
Trend lines smooth out spikes, defeating the purpose of anomaly detection.
- ✗
Increase the size of the data points to make them more visible
Why it's wrong here
Larger markers increase overlap and clutter.
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