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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, youll discover how to: Test drive your data to see if its ready for analysis Work spreadsheet data into a usable form Handle encoding problems that lurk in text data Develop a successful web-scraping effort Use NLP tools to reveal the real sentiment of online reviews Address cloud computing issues that can impact your analysis effort Avoid policies that create data analysis roadblocks Take a systematic approach to data quality analysis About the Author Q Ethan McCallum is a consultant, writerand technology enthusiast, though perhaps not in that order. His work has appeared online on The Reilly Network and Java.netand also in print publications such as C/C++ Users Journal, Doctor Dobbs Journaland Linux Magazine. In his professional roles, he helps companies to make smart decisions about data and technology.