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Data Visualization

Seven Common Data Visualization Mistakes

Small design choices can make a report harder to read. These common mistakes are easy to fix once you know what to look for.

May 19, 20268 min read

The seven mistakes

Most visualization problems are not about aesthetics; they make information harder to understand. Here are seven that appear frequently.

  • Using the wrong chart type for the question being asked
  • Overloading a single chart with too many series
  • Relying on color alone to convey meaning
  • Truncating axes in ways that exaggerate change
  • Leaving charts unlabeled or without context
  • Using inconsistent colors across a report
  • Adding decoration that competes with the data

Guiding principles

A few principles help avoid most of these issues: choose the chart that fits the question, label clearly, use color with purpose, and remove anything that does not help the reader.

Key takeaways

  • Chart choice should match the question.
  • Color and labeling carry meaning and should be used deliberately.
  • Removing clutter improves comprehension.

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