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:

Test drive your data to see if it’s 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

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