Beautiful Data: The Stories Behind Elegant Data Solutions (Google eBook)

Front Cover
"O'Reilly Media, Inc.", Jul 14, 2009 - Computers - 386 pages
18 Reviews

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
  •   

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    Review: Beautiful Data: The Stories Behind Elegant Data Solutions (Theory In Practice)

    User Review  - Andrew Magee - Goodreads

    Lots of interesting stuff, though lots of annoying and tiresome filler. Read full review

    Review: Beautiful Data: The Stories Behind Elegant Data Solutions (Theory In Practice)

    User Review  - Andrew Doran - Goodreads

    Thought-provoking collection of essays about different aspects of data. The book was a bit slow to start but soon picked up and covered a variety of thought-provoking topics. Although I feel that it ... Read full review

    Contents

    Seeing Your Life in Data
    1
    Keeping Users in Mind When Designing Data Collection Methods
    17
    Embedded Image Data Processing on Mars
    35
    Cloud Storage Design in a PNUTShell
    55
    Information Platforms and the Rise of the Data Scientist
    73
    The Geographic Beauty of a Photographic Archive
    85
    Data Finds Data
    105
    Portable Data in Real Time
    119
    What Data Doesnt Do
    205
    Natural Language Corpus Data
    219
    The Story of DNA
    243
    Beautifying Data in the Real World
    259
    Exploring Millions of Social Stereotypes
    279
    The Effect of the Housing Crisis
    303
    Beautiful Political Data
    323
    Connecting Data
    335

    Surfacing the Deep Web
    133
    Building Radioheads House of Cards
    149
    Visualizing Urban Data
    167
    The Design of Senseus
    183
    Contributors
    349
    Index
    357
    Copyright

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    About the author (2009)

    Toby Segaran is the author of Programming Collective Intelligence, a very popular O'Reilly title. He was the founder of Incellico, a biotech software company later acquired by Genstruct. He currently holds the title of Data Magnate at Metaweb Technologies and is a frequent speaker at technology conferences.

    Jeff Hammerbacher is the Vice President of Products and Chief Scientist at Cloudera. Jeff was an Entrepreneur in Residence at Accel Partners immediately prior to joining Cloudera. Before Accel, he conceived, built, and led the Data team at Facebook. The Data team was responsible for driving many of the statistics and machine learning applications at Facebook, as well as building out the infrastructure to support these tasks for massive data sets. The team produced several academic papers and two open source projects: Hive, a system for offline analysis built above Hadoop, and Cassandra, a structured storage system on a P2P network. Before joining Facebook, Jeff was a quantitative analyst on Wall Street. Jeff earned his Bachelor's Degree in Mathematics from Harvard University.

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