Bad Data Handbook: Cleaning Up The Data So You Can Get Back To Work (Paperback)

Q. Ethan McCallum



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


什麼是壞數據?有些人認為它是一個技術現象,例如缺失值或格式錯誤的記錄,但壞數據包含更多內容。在這本手冊中,數據專家Q. Ethan McCallum邀請了來自數據領域各個角落的19位同事,揭示了他們如何從糟糕的數據問題中恢復過來。



- 測試數據以確定是否適合進行分析
- 將試算表數據轉換為可用形式
- 處理文本數據中潛藏的編碼問題
- 開展成功的網絡爬蟲工作
- 使用自然語言處理工具揭示網絡評論的真實情感
- 解決可能影響分析工作的雲計算問題
- 避免創造數據分析障礙的政策
- 採取系統化的方法進行數據質量分析