T�tulo: Making Data Visual: A Practical Guide to Using Visualization for Insight
Editor: O'Reilly Media (edition 1)
Fecha de publicaci�n: 2018
Idioma: Ingl�s
ISBN 10: 1491928468
ISBN 13: 9781491928462
Encuadernaci�n: Paperback
Edici�n: 1.
Estado: Very Good

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Sinopsis

You have a mound of data front of you and a suite of computation tools at your disposal. Which parts of the data actually matter? Where is the insight hiding? If you� re a data scientist trying to navigate the murky space between data and insight, this practical book shows you how to make sense of your data through high-level questions, well-defined data analysis tasks, and visualizations to clarify understanding and gain insights along the way.

When incorporated into the process early and often, iterative visualization can help you refine the questions you ask of your data. Authors Danyel Fisher and Miriah Meyer provide detailed case studies that demonstrate how this process can evolve in the real world.

You� ll learn:

The data counseling process for moving from general to more precise questions about your data, and arriving at a working visualization
The role that visual representations play in data discovery
Common visualization types by the tasks they fulfill and the data they use
Visualization techniques that use multiple views and interaction to support analysis of large, complex data sets

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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.

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