Making data visual: A practical session on using visualization for insight

Description

You have a mound of data sitting in front of you and a suite of computation tools at your disposal. And yet, you’re stumped as to how to turn that data into insight. While data science case studies demonstrate how organizations have made billions of dollars by looking at the right dimensions, it can be difficult to figure out which dimensions are the right ones.

Using hands-on exercises, Danyel Fisher and Miriah Meyer outline a technique for filling this gap that treats data science as a holistic endeavor, one that combines knowledge about what is technically possible with a human-centered sensibility. In a discussion grounded in a description of fundamental visualization design patterns (which informs how we think about data, the questions we ask of it, and what we can do with it), Danyel and Miriah explain how to form questions and transform data in order to support human-driven data exploration. They also teach visualization patterns, each of which offers a different perspective on data and answers different questions. You’ll learn about data counseling, which allows users to conceptualize and shape their data into one of these patterns, as well as a taxonomy of visualizations for common data types, techniques for gathering design requirements, and references for when and where to make use of statistical methods.