Written by leaders in the field, this book introduces foundational principles and modern practices that treat data transformation with the same discipline as software development—equal parts theory and hands-on implementation. With guidance on everything from building reproducible, testable workflows to deploying industrial-grade frameworks, the book equips data professionals with the knowledge to tackle real-world challenges in analytics, machine learning, and AI. Squarely focusing on reliability and scale, the authors deliver essential strategies for turning raw data into fresh, trustworthy insights.
AI Reading Assistant
Summary and highlights from this book's index; jump to passages in the text
Loading comments...
Reply to Comment
Edit Comment