Beautiful Data

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Synopsis

In this insightful book, you'll learn from the best data practitioners in the field just how wide-ranging -- and beautiful -- working with data can be. Join 39 contributors as they explain how they developed simple and elegant solutions on projects ranging from the Mars lander to a Radiohead video.

With Beautiful Data, you will:

Explore the opportunities and challenges involved in working with the vast number of datasets made available by the Web
Learn how to visualize trends in urban crime, using maps and data mashups
Discover the challenges of designing a data processing system that works within the constraints of space travel
Learn how crowdsourcing and transparency have combined to advance the state of drug research
Understand how new data can automatically trigger alerts when it matches or overlaps pre-existing data
Learn about the massive infrastructure required to create, capture, and process DNA data

That's only small sample of what you'll find in Beautiful Data. For anyone who handles data, this is a truly fascinating book. Contributors include:

Nathan Yau
Jonathan Follett and Matt Holm
J.M. Hughes
Raghu Ramakrishnan, Brian Cooper, and Utkarsh Srivastava
Jeff Hammerbacher
Jason Dykes and Jo Wood
Jeff Jonas and Lisa Sokol
Jud Valeski
Alon Halevy and Jayant Madhavan
Aaron Koblin with Valdean Klump
Michal Migurski
Jeff Heer
Coco Krumme
Peter Norvig
Matt Wood and Ben Blackburne
Jean-Claude Bradley, Rajarshi Guha, Andrew Lang, Pierre Lindenbaum, Cameron Neylon, Antony Williams, and Egon Willighagen
Lukas Biewald and Brendan O'Connor
Hadley Wickham, Deborah Swayne, and David Poole
Andrew Gelman, Jonathan P. Kastellec, and Yair Ghitza
Toby Segaran