Bad Data Handbook
What is bad data? Some people consider it a technical phenomenon, like missing values or malformed records, but bad data includes a lot more. In this handbook, data expert Q. Ethan McCallum has gathered 19 colleagues from every corner of the data arena to reveal how they’ve recovered from nasty data problems.
From cranky storage to poor representation to misguided policy, there are many paths to bad data. Bottom line? Bad data is data that gets in the way. This book explains effective ways to get around it.
Among the many topics covered, you’ll discover how to:
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What Is Bad Data?
Chapter 2 Is It Just Me or Does This Data Smell Funny?
Chapter 3 Data Intended for Human Consumption Not Machine Consumption
Chapter 4 Bad Data Lurking in Plain Text
Chapter 5 ReOrganizing the Webs Data
Chapter 6 Detecting Liars and the Confused in Contradictory Online Reviews
Chapter 7 Will the Bad Data Please Stand Up?
Chapter 8 Blood Sweat and Urine
A Guide for When to Stick to Files
Chapter 13 Crouching Table Hidden Network
Chapter 14 Myths of Cloud Computing
Chapter 15 The Dark Side of Data Science
Chapter 16 How to Feed and Care for Your MachineLearning Experts
Chapter 17 Data Traceability
Knowing When Your Data Is Good Enough