AI for Data Cleaning

Real data is never clean-it lands with missing values, duplicate rows, inconsistent formats, and structural chaos. Data cleaning has long been the thankless bottleneck of analytics, soaking up hours that should go to insight. This book shows you how to partner with AI to slash that drudgery. You'll learn to brief a language model to profile your dataset, find anomalies, suggest schema transformations, and generate auditable cleaning scripts-all while keeping your hand on the reviewer's pen. Every chapter emphasizes verification: AI output is a draft, never the final word. Through worked examples and practical checklists, you'll build a repeatable workflow that makes cleaning faster without sacrificing trust. The author, Daniel Osei Vance, draws on years of wrangling messy administrative data to give you battle-tested strategies-not hype. Whether you wrangle CSV files daily or maintain a production pipeline, this guide will turn the unglimorous work into a streamlined, reproducible habit that frees you to focus on analysis. Part of The AI Maker Library.

About the author

Daniel Osei Vance writes for The AI Maker Library.