Share Data Through the Art of Visualization
Core concepts
Visualization translates findings into something an audience can act on. Match the chart to the question: bar charts compare categories, line charts show change over time, pie charts show parts of a whole (only with a few slices), scatter plots reveal relationships between two numeric variables, and histograms show the distribution of one numeric variable across bins.
Design uses preattentive attributes - color, size, position, and orientation - which the eye processes before conscious thought. Use them deliberately: highlight the point you want noticed and mute everything else. Follow the McCandless method when presenting: name the visualization, state what the data represents, explain why it matters, and note any caveats or biases.
Understand storytelling structure: characters (the audience), a setting and plot (the data and the question), and a call to action. Know the difference between dashboards (interactive, monitored over time, filterable) and static reports (a snapshot for a specific audience at a specific moment). Accessibility matters: sufficient contrast, readable labels, and never relying on color alone to carry meaning.
Traps
Distractors push pie charts with many slices or 3-D effects that distort proportion. Questions also swap scatter and histogram, or claim a dashboard is the right deliverable when the audience needs a one-time static summary. Beware visualizations that truncate the y-axis without disclosure.
Rule of thumb
Ask what the audience must compare or see change. Change over time maps to a line, category comparison to a bar, distribution to a histogram, and relationship to a scatter.