- Bad Data Handbook
- About the Authors
- Preface
- 1. Setting the Pace: What Is Bad Data?
- 2. Is It Just Me, or Does This Data Smell Funny?
- 3. Data Intended for Human Consumption, Not Machine Consumption
- 4. Bad Data Lurking in Plain Text
- 5. (Re)Organizing the Web’s Data
- 6. Detecting Liars and the Confused in Contradictory Online Reviews
- 7. Will the Bad Data Please Stand Up?
- 8. Blood, Sweat, and Urine
- 9. When Data and Reality Don’t Match
- 10. Subtle Sources of Bias and Error
- 11. Don’t Let the Perfect Be the Enemy of the Good: Is Bad Data Really Bad?
- 12. When Databases Attack: A Guide for When to Stick to Files
- 13. Crouching Table, Hidden Network
- 14. Myths of Cloud Computing
- Introduction to the Cloud
- What Is “The Cloud”?
- The Cloud and Big Data
- Introducing Fred
- At First Everything Is Great
- They Put 100% of Their Infrastructure in the Cloud
- As Things Grow, They Scale Easily at First
- Then Things Start Having Trouble
- They Need to Improve Performance
- Higher IO Becomes Critical
- A Major Regional Outage Causes Massive Downtime
- Higher IO Comes with a Cost
- Data Sizes Increase
- Geo Redundancy Becomes a Priority
- Horizontal Scale Isn’t as Easy as They Hoped
- Costs Increase Dramatically
- Fred’s Follies
- Myth 1: Cloud Is a Great Solution for All Infrastructure Components
- Myth 2: Cloud Will Save Us Money
- Myth 3: Cloud IO Performance Can Be Improved to Acceptable Levels Through Software RAID
- Myth 4: Cloud Computing Makes Horizontal Scaling Easy
- Conclusion and Recommendations
- 15. The Dark Side of Data Science
- 16. How to Feed and Care for Your Machine-Learning Experts
- 17. Data Traceability
- 18. Social Media: Erasable Ink?
- 19. Data Quality Analysis Demystified: Knowing When Your Data Is Good Enough
- Index
- About the Author
- Colophon
- Copyright
About the Author
Q Ethan McCallum is a consultant, writer, and technology enthusiast, though perhaps not in that order. His work has appeared online on The O’Reilly Network and Java.net, and also in print publications such as C/C++ Users Journal, Doctor Dobb’s Journal, and Linux Magazine. In his professional roles, he helps companies to make smart decisions about data and technology.
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