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Beautiful Data

Cover of Beautiful Data by Jeff Hammerbacher... Published by O'Reilly Media, Inc.
  1. Beautiful Data
    1. SPECIAL OFFER: Upgrade this ebook with O’Reilly
    2. A Note Regarding Supplemental Files
    3. Preface
      1. How This Book Is Organized
      2. Conventions Used in This Book
      3. Using Code Examples
      4. How to Contact Us
      5. Safari® Books Online
    4. 1. Seeing Your Life in Data
      1. Personal Environmental Impact Report (PEIR)
      2. your.flowingdata (YFD)
      3. Personal Data Collection
      4. Data Storage
      5. Data Processing
      6. Data Visualization
      7. The Point
      8. How to Participate
    5. 2. The Beautiful People: Keeping Users in Mind When Designing Data Collection Methods
      1. Introduction: User Empathy Is the New Black
      2. The Project: Surveying Customers About a New Luxury Product
      3. Specific Challenges to Data Collection
      4. Designing Our Solution
      5. Results and Reflection
    6. 3. Embedded Image Data Processing on Mars
      1. Abstract
      2. Introduction
      3. Some Background
      4. To Pack or Not to Pack
      5. The Three Tasks
      6. Slotting the Images
      7. Passing the Image: Communication Among the Three Tasks
      8. Getting the Picture: Image Download and Processing
      9. Image Compression
      10. Downlink, or, It's All Downhill from Here
      11. Conclusion
    7. 4. Cloud Storage Design in a PNUTShell
      1. Introduction
      2. Updating Data
      3. Complex Queries
      4. Comparison with Other Systems
      5. Conclusion
      6. Acknowledgments
      7. References
    8. 5. Information Platforms and the Rise of the Data Scientist
      1. Libraries and Brains
      2. Facebook Becomes Self-Aware
      3. A Business Intelligence System
      4. The Death and Rebirth of a Data Warehouse
      5. Beyond the Data Warehouse
      6. The Cheetah and the Elephant
      7. The Unreasonable Effectiveness of Data
      8. New Tools and Applied Research
      9. MAD Skills and Cosmos
      10. Information Platforms As Dataspaces
      11. The Data Scientist
      12. Conclusion
    9. 6. The Geographic Beauty of a Photographic Archive
      1. Beauty in Data: Geograph
      2. Visualization, Beauty, and Treemaps
      3. A Geographic Perspective on Geograph Term Use
      4. Beauty in Discovery
      5. Reflection and Conclusion
      6. Acknowledgments
      7. References
    10. 7. Data Finds Data
      1. Introduction
      2. The Benefits of Just-in-Time Discovery
      3. Corruption at the Roulette Wheel
      4. Enterprise Discoverability
      5. Federated Search Ain't All That
      6. Directories: Priceless
      7. Relevance: What Matters and to Whom?
      8. Components and Special Considerations
      9. Privacy Considerations
      10. Conclusion
    11. 8. Portable Data in Real Time
      1. Introduction
      2. The State of the Art
      3. Social Data Normalization
      4. Conclusion: Mediation via Gnip
    12. 9. Surfacing the Deep Web
      1. What Is the Deep Web?
      2. Alternatives to Offering Deep-Web Access
      3. Conclusion and Future Work
      4. References
    13. 10. Building Radiohead's House of Cards
      1. How It All Started
      2. The Data Capture Equipment
      3. The Advantages of Two Data Capture Systems
      4. The Data
      5. Capturing the Data, aka "The Shoot"
      6. Processing the Data
      7. Post-Processing the Data
      8. Launching the Video
      9. Conclusion
    14. 11. Visualizing Urban Data
      1. Introduction
      2. Background
      3. Cracking the Nut
      4. Making It Public
      5. Revisiting
      6. Conclusion
    15. 12. The Design of
      1. Visualization and Social Data Analysis
      2. Data
      3. Visualization
      4. Collaboration
      5. Voyagers and Voyeurs
      6. Conclusion
      7. References
    16. 13. What Data Doesn't Do
      1. When Doesn't Data Drive?
      2. Conclusion
      3. References
    17. 14. Natural Language Corpus Data
      1. Word Segmentation
      2. Secret Codes
      3. Spelling Correction
      4. Other Tasks
      5. Discussion and Conclusion
      6. Acknowledgments
    18. 15. Life in Data: The Story of DNA
      1. DNA As a Data Store
      2. DNA As a Data Source
      3. Fighting the Data Deluge
      4. The Future of DNA
      5. Acknowledgments
    19. 16. Beautifying Data in the Real World
      1. The Problem with Real Data
      2. Providing the Raw Data Back to the Notebook
      3. Validating Crowdsourced Data
      4. Representing the Data Online
      5. Closing the Loop: Visualizations to Suggest New Experiments
      6. Building a Data Web from Open Data and Free Services
      7. Acknowledgments
      8. References
    20. 17. Superficial Data Analysis: Exploring Millions of Social Stereotypes
      1. Introduction
      2. Preprocessing the Data
      3. Exploring the Data
      4. Age, Attractiveness, and Gender
      5. Looking at Tags
      6. Which Words Are Gendered?
      7. Clustering
      8. Conclusion
      9. Acknowledgments
      10. References
    21. 18. Bay Area Blues: The Effect of the Housing Crisis
      1. Introduction
      2. How Did We Get the Data?
      3. Geocoding
      4. Data Checking
      5. Analysis
      6. The Influence of Inflation
      7. The Rich Get Richer and the Poor Get Poorer
      8. Geographic Differences
      9. Census Information
      10. Exploring San Francisco
      11. Conclusion
      12. References
    22. 19. Beautiful Political Data
      1. Example 1: Redistricting and Partisan Bias
      2. Example 2: Time Series of Estimates
      3. Example 3: Age and Voting
      4. Example 4: Public Opinion and Senate Voting on Supreme Court Nominees
      5. Example 5: Localized Partisanship in Pennsylvania
      6. Conclusion
      7. References
    23. 20. Connecting Data
      1. What Public Data Is There, Really?
      2. The Possibilities of Connected Data
      3. Within Companies
      4. Impediments to Connecting Data
      5. Possible Solutions
      6. Conclusion
    24. A. Contributors
    25. Index
    26. About the Authors
    27. COLOPHON
    28. SPECIAL OFFER: Upgrade this ebook with O’Reilly

Corruption at the Roulette Wheel

This is a true story where bad-guy data finds good-guy data—causing an unexpected discovery and resulting in a surprise outcome.

In the mid-1990s, riverboat gaming became legalized in many new jurisdictions, Louisiana being one of them. One of the challenges of a new gaming jurisdiction is the lack of available local employee candidates with deep gaming experience. New jurisdictions must therefore train the local workforce in a wide range of specialty job categories, ranging from dealers to surveillance room operators. Bossier City, Louisiana is one such community that had to make the transition from no casino business to casino riverboat operations.

Today is like any other day in any other casino. The dealers are watching the players. The floor supervisors are watching the dealers and the players. The casino manager is watching the floor supervisors, the dealers, and the players. And the surveillance room is watching everyone—even the casino executives. The surveillance room has an obligation to watch gaming transactions, not only to protect the house but also to protect the customers. Surveillance focuses both on gambling transactions as well as evidence of other criminal activity. For example, a purse-snatcher is bad for business because he interferes with the customer experience.

Surveillance is the last line of defense.

Hundreds of cameras (thousands in the Vegas mega-casinos) are piped into a remarkably tiny surveillance room. Twenty, thirty, maybe ...

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