By Monks for the Lesser Mortals

Let me introduce Building Effective Data Science Practices - a book by Vineet Raina and Srinath Krishnamurthy - one of the first books I read at the beginning of my journey into GenAI. The authors are my colleagues.

In my early GenAI days, I wanted to know the fundamental principles that make it work. I was curious about how these machines actually learn. That’s when I came across the world of Data Science and Data Engineering, and decided to read the book. Well, the book was there in our library, but I never ventured to read it because I thought it would be too complex for me to understand—which turned out to be an incorrect assumption.

The theme of the book is the Data Science Process: how the process can help solve concrete problems, the techniques and tools used in the process, and the practical aspects of building teams and executing projects.

A parallel theme that accompanies you throughout is that of two distinct data science cultures: Monks and Wild-West. The cultures influence the approach and the goals through the entire process. Most of us are from this Wild-West culture, seeking immediate gratification for our efforts. The Monks, on the other hand, are truth seekers; they are not in a rush to get the rewards, look for the truth in the data at every step, use their energy to identify eternal patterns, maintain the sanctity of data, and strive for purity of models. Whereas, the mortals from the Wild-West culture are mainly interested in building data models quickly and are happy if the models' predictions are accurate “enough” for now. 

The book is written in plain language, if you do not mind occasional words creeping in such as “praxis”. Its strength lies in abundance of real world examples and its focus on a few algorithms. I found enough details to get a bird's eye view of data science and engineering in practice.