Selecting a Visual Analytics Application

Professor Pat Hanrahan, Stanford University and Chief Scientist - Tableau Software,

Visual analytics is becoming the fastest way for people to explore and understand data of any size. Read our definitive guide for selecting a visual analytics, or data visualization, software application.

Based on the 7 defining characteristics of visual analytics, this white paper will tell you exactly what to look for and how to evaluate applications.

You’ll learn:

  • How visual analysis software supports the cycle of visual analysis
  • Why visual analysis helps humans process data and information more rapidly
  • The importance of multi-dimensional visual expressiveness
  • How automatic data visualization significantly reduces work time and helps people think visually
  • Why being able to shift perspectives on data is so critical to understanding
  • How linking perspectives across dashboards and views makes analysis faster and more effective
  • Why data visualization naturally extends collaboration across your organization

For each essential element, you’ll learn exactly the questions to ask application vendors about their visual analytics capabilities. The paper includes actual examples of organizations all over the world using visual analytics.

About the author

Professor Pat Hanrahan, Stanford University and Chief Scientist - Tableau Software