Data Visualization

A practical example

Example: a pipeline report shows twelve funnel stages as a pie chart; nobody can compare similar-sized slices.

Rebuilt as a horizontal bar chart sorted by volume, with stage-to-stage drop-off annotated, the same data makes the bottleneck obvious in five seconds.

What to evaluate before investing

• Ask whether the tool supports the chart types your metrics need, like cohort grids or funnel bars.
• Check whether defaults mislead: truncated axes, dual axes or pie charts with many slices.
• Test how easily a non-technical stakeholder can read a chart without a presenter explaining it.

Limitations and tradeoffs

Tradeoff: visual polish can mislead as easily as clarify. Emphasizing one metric with color or scale choices shapes conclusions, so teams need shared conventions about honest defaults rather than treating every chart as neutral.