In the past six years of working in data science, I have made all the mistakes described in this book. Every time, it cost me hours, sometimes days to figure out what the problem was and to fix it. This type of iterative work is what data scientists mean when they talk about how they spend most of their time on data preparation. Yet, for some reason, the art of preparing data and ensuring a sufficiently high level of quality is largely ignored by textbooks, university programs, online courses and industry conferences. That's why I felt the need to write this book and share some of my experiences. It is the hands-on advice that I myself wish I had when I started my career as a data scientist.