Data Services

Some well-known data visualization tools:

• Tableau Public
• Power BI - available in your campus-provided Office 365 resources
• Google Data Studio

Note that many dataset and data resources contain their own data visualization options that may be easier-to-use since they are integrated.

Do you need a data visualization?

• If the significance of the data can be concisely expressed with statistics, then you may not need a data visualization.

What's the right data visualization for your work?

• Who is the audience?
• Focus on reducing the cognitive load.
• Avoid too much data.
• Avoid 3D visualizations.
• Utilize a tool that helps with identifying suitable data visualizations for your needs, such as Data Viz Project.

Ethically represent the data.

• Don't distort the range of data represented.
• Don't cherry pick what is represented by the data visualization.
• Clearly label the data.

Think about colors.

• According to the National Eye Institute, 1 in 12 men and 1 in 200 women have color vision deficiencies.  Using colors alone to express data prevents some from understanding the data being visualized.
  • Utilize colorblind friendly color combinations
  • "Use different shapes, patterns, textures, or labels" (Ferreira)
• "High-contract color pairings cause viewers to perceive greater degrees of data disparity." (Bowers)

Tell a Story

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Reference

Numbers Shouldn't Lie: An Overview of Common Data Visualization Mistakes (Micah Bowers)

Two Simple Steps to Create Colorblind-Friendly Data Visualizations (CR Ferreira)