Data Visualization and Reporting
The Data Visualization and Reporting domain tests how to choose charts, encode values honestly, and deliver reports that support decisions. Expect scenario questions on chart fitness, misleading design, dashboards and audience.
Chart choice
Use bar charts for comparing categories, line charts for trends over time, scatter plots for relationships between two numeric variables, histograms for distributions, and box plots for spread and outliers. Pie charts work only for a few parts of one whole; many slices become unreadable. Tables suit precise lookup, while dashboards suit monitoring KPIs.
Honest encoding
Position and length are easier to compare than angle, area or volume. Start quantitative axes at zero unless the chart is a line chart showing change, and label any non-zero baseline. Avoid truncated axes, inverted axes, inconsistent intervals, 3D effects and dual axes that invite false comparisons. Color should support, not carry, meaning: use a colorblind-safe palette, sufficient contrast, direct labels and text alternatives. Data-ink should serve the message; remove decoration that does not.
Reporting and narrative
Reporting translates analysis into decisions. State the audience, the question, the finding, the evidence, the limitation and the recommended action. A dashboard needs a clear hierarchy: headline KPIs, trends, then diagnostic detail. Storytelling is not embellishment; it is ordered evidence.
Worked example
Monthly sales by region are shown as a bar chart sorted descending, with a zero baseline and direct value labels. If the question changes to sales trend over 24 months, use a line chart with monthly points and annotate promotions. Reasoning: the comparison is categorical, so bars preserve length; time is continuous, so a line shows direction. A pie chart with 12 regions would fail.
Traps
Truncated axes exaggerate differences; dual axes imply relationships that may not exist; color-only encoding excludes some readers. Too many pie slices, 3D charts and vanity metrics without decision value are frequent distractors.