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Data Visualization

Tips, tricks and tools for visualizing data

Infographics vs. Data Visualization

While infographics and data visualizations both visually encode information, the terms aren’t necessarily interchangeable:


Data Visualizations

  • Developed for a particular dataset
  • Context-sensitive
  • Hand-crafted
  • Tend to be more subjective, pitching a specific point of view
  • Well-suited for resumes, marketing content and blog posts
  • Existing techniques with general applications
  • Context-free
  • (Largely) automatically generated
  • Tend to be more objective, positioning itself as an analytics tool
  • Well-suited for dashboards and research reports

For example, we can consider “Women in Tech” an infographic because it introduces a clear viewpoint: although women are gaining ground in tech, they still lack representation. We notice that certain design elements, such as traditionally feminine colors, are hand-picked to enhance the storytelling. Further, the choice and order of charts would not be compatible with any other dataset.

Women in tech infographic

Image credit:​

On the other hand, “The Daily Routines of Famous Creative People” is a data visualization. The graphic is not promoting a specific conclusion; rather, it allows the viewer to assess different lifestyles and draw their own conclusions. One could easily replace the dataset with lifestyle data about other groups of people, and the visualization technique would still hold. In practice, of course, the distinction between infographic and data visualization can be much more subtle.

Image credit:​

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