Beautiful Data

Informationen zum Autor 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. Klappentext 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 Zusammenfassung Helps you explore the opportunities and challenges involved in working with the many number of datasets made available by the Web. This book also helps you learn how to visualize trends in urban crime, using maps and data mashups, and discover the challenges of designing a data processing system that works within the constraints of space travel. Inhaltsverzeichnis Dedication Preface Chapter 1: Seeing Your Life in Data Chapter 2: The Beautiful People: Keeping Users in Mind When Designing Data Collection Methods Chapter 3: Embedded Image Data Processing on Mars Chapter 4: Cloud Storage Design in a PNUTShell Chapter 5: Information Platforms and the Rise of the Data Scientist Chapter 6: The Geographic Beauty of a Photographic Archive Chapter 7: Data Finds Data Chapter 8: Portable Data in Real Time Chapter 9: Surfacing the Deep Web Chapter 10: Building Radiohead's House of Cards Chapter 11: Visual...

List of contents

From the contents:

Chapter 1 Seeing Your Life in Data

Personal Environmental Impact Report (PEIR)

your.flowingdata (YFD)

Personal Data Collection

Data Storage

Data Processing

Data Visualization

The Point

How to Participate

Chapter 2 The Beautiful People: Keeping Users in Mind When Designing Data Collection Methods

Introduction: User Empathy Is the New Black

The Project: Surveying Customers About a New Luxury Product

Specific Challenges to Data Collection

Designing Our Solution

Results and Reflection

Chapter 3 Embedded Image Data Processing on Mars

Abstract

Introduction

Some Background

To Pack or Not to Pack

The Three Tasks

Slotting the Images

Passing the Image: Communication Among the Three Tasks

Getting the Picture: Image Download and Processing

Image Compression

Downlink, or, It's All Downhill from Here

Conclusion

Chapter 4 Cloud Storage Design in a PNUTShell

Introduction

Updating Data

Complex Queries

Comparison with Other Systems

Conclusion

Acknowledgments

References

Chapter 5 Information Platforms and the Rise of the Data Scientist

Libraries and Brains

Facebook Becomes Self-Aware

A Business Intelligence System

The Death and Rebirth of a Data Warehouse

Beyond the Data Warehouse

The Cheetah and the Elephant

The Unreasonable Effectiveness of Data

New Tools and Applied Research

MAD Skills and Cosmos

Information Platforms As Dataspaces

The Data Scientist

Conclusion

Chapter 6 The Geographic Beauty of a Photographic Archive

Beauty in Data: Geograph

Visualization, Beauty, and Treemaps

A Geographic Perspective on Geograph Term Use

Beauty in Discovery

Reflection and Conclusion

Acknowledgments

References

Chapter 7 Data Finds Data

Introduction

The Benefits of Just-in-Time Discovery

Corruption at the Roulette Wheel

Enterprise Discoverability

Federated Search Ain't All That

Directories: Priceless

Relevance: What Matters and to Whom?

Components and Special Considerations

Privacy Considerations

Conclusion

Chapter 8 Portable Data in Real Time

Introduction

The State of the Art

Social Data Normalization

Conclusion: Mediation via Gnip

Chapter 9 Surfacing the Deep Web

What Is the Deep Web?

Alternatives to Offering Deep-Web Access

Conclusion and Future Work

References

Chapter 10 Building Radiohead's House of Cards How It All Started

The Data Capture Equipment

The Advantages of Two Data Capture Systems

The Data

Capturing the Data, aka "The Shoot"

Processing the Data

Post-Processing the Data

Launching the Video

Conclusion

Chapter 11 Visualizing Urban Data

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Product details

• Authors: Jeff Hammerbacher, Toby Segaran, Segaran Toby
• Assisted by: Jeff Hammerbacher (Editor), Toby Segaran (Editor)
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Paperback / Softback
• Released: 31.07.2009
• EAN: 9780596157111
• ISBN: 978-0-596-15711-1
• Series: THEORY IN PRACTICE
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; COMPUTERS / Programming / General, Databases, COMPUTERS / Database Administration & Management, streaming, visualization, management, data, analysis, data visualization storage management analysis streaming