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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. Which part of that data actually matters, and where is this insight hidden?
If you’re a data scientist who struggles to navigate the murky space between data and insight, this book will help you think about and reshape data for visual data exploration. It’s ideal for relatively new data scientists, who may be computer-knowledgeable and data-knowledgeable, but do not yet know how to create effective, explorable representations of data.
With this book, you’ll learn:
Task analysis, driven by a series of leading questions that draw out the important aspects of the data to be explored
Visualization patterns, each of which take a different perspective on data and answer different questions
A taxonomy of visualizations for common data types
Techniques for gathering design requirements
When and where to make use of statistical methods
Chapter 2Operationalization, from questions to data
Chapter 3Components of a Visualization
Chapter 4Data Counseling
Chapter 5Single Views
Chapter 6Multiple and Coordinated Views
Chapter 7Case Studies
Chapter 8Design Process
Chapter 10Data in the Real World: Getting, Cleaning, and Shaping
Miriah Meyer is an assistant professor at the University of Utah, where she runs the Visualization Design Lab. Her work focuses on designing visualizations for researchers and scholars that help them make sense of complex data. Miriah has collaborated with experts in a broad range of fields, including biology, geography, and poetry. She earned a PhD from the University of Utah in 2008, and worked as a postdoctoral research fellow at Harvard University until 2011.
Danyel Fisher is a Senior Researcher at Microsoft Research; his work centers on information and data visualization. His work focuses on how users can make use of visualization to better make sense of their data; his work supports data analysts, end-users, and people who just happen to have had a lot of information dumped in their laps. His research perspective starts from a background is in human-computer interaction. Danyel received his MS from UC Berkeley in 2000, and his PhD from UC Irvine in 2004.