Beautiful Data: The Stories Behind Elegant Data Solutions

Overview

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 ...
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Beautiful Data: The Stories Behind Elegant Data Solutions

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Overview

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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Product Details

  • ISBN-13: 9780596157111
  • Publisher: O'Reilly Media, Incorporated
  • Publication date: 8/15/2009
  • Pages: 364
  • Sales rank: 622,215
  • Product dimensions: 7.00 (w) x 9.10 (h) x 1.00 (d)

Meet the Author

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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Table of Contents


DedicationPrefaceChapter 1: Seeing Your Life in DataChapter 2: The Beautiful People: Keeping Users in Mind When Designing Data Collection MethodsChapter 3: Embedded Image Data Processing on MarsChapter 4: Cloud Storage Design in a PNUTShellChapter 5: Information Platforms and the Rise of the Data ScientistChapter 6: The Geographic Beauty of a Photographic ArchiveChapter 7: Data Finds DataChapter 8: Portable Data in Real TimeChapter 9: Surfacing the Deep WebChapter 10: Building Radiohead's House of CardsChapter 11: Visualizing Urban DataChapter 12: The Design of Sense.usChapter 13: What Data Doesn't DoChapter 14: Natural Language Corpus DataChapter 15: Life in Data: The Story of DNAChapter 16: Beautifying Data in the Real WorldChapter 17: Superficial Data Analysis: Exploring Millions of Social StereotypesChapter 18: Bay Area Blues: The Effect of the Housing CrisisChapter 19: Beautiful Political DataChapter 20: Connecting DataContributorsCOLOPHON
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