<DIV><p>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.</p><p>From cranky storage to poor representation to misguided policy, there are many paths to bad data. Bottom line? Bad data is <i>data that gets in the way</i>. This book explains effective ways to get around it.</p><p>Among the many topics covered, you’ll discover how to:</p><ul><li>Test drive your data to see if it’s ready for analysis </li><li>Work spreadsheet data into a usable form </li><li>Handle encoding problems that lurk in text data </li><li>Develop a successful web-scraping effort </li><li>Use NLP tools to reveal the real sentiment of online reviews </li><li>Address cloud computing issues that can impact your analysis effort </li><li>Avoid policies that create data analysis roadblocks </li><li>Take a systematic approach to data quality analysis </li></ul></div>