My Top Five Data Science Reads of 2018

“Reading is essential for those who seek to rise above the ordinary.” — Jim Rohn

Data Science is an emerging field, and everybody is trying to hone their skills to master it. People are curious about the vital ingredients needed to become a ‘good’ Data Scientist. I believe a sound understanding of statistics, good command over tools like R/Python, being able to spot patterns in data, ability to apply accurate models are few of the many traits that are required. However being good is one thing and being successful is another. A ‘successful’ data scientist not only focuses on the necessary tools and concepts but also remains abreast with the current trends in the industry.

Books are an excellent way to build a better perspective and extend the horizons of imagination. Despite the plethora of Data Science resources available on the internet, books help to develop a deeper understanding of the subject and can be used as a ready reference, whenever required.

I have a passion for both books and data. So, this year, I picked five books that were not the “typical” Data science types but nevertheless `beneficial in the Data Science domain. Not only they enhanced my knowledge but also gave me a lot of food for thought about the field of Data. Well if you are an aspiring Data Scientist and looking for something to read for that lazy afternoon, here is a list that I would recommend.

Skin in the Game: The Hidden Asymmetries in Daily Life

Nassim Nicholas Taleb is one of the foremost thinkers of our time. The phrase “skin in the game” is the backbone of risk management but applies to all domains including Data Science. If you have skin in the game, you’re more likely to draw on your local knowledge, use what is important and discard what is irrelevant.

How is it applicable to Data Science? This book deals with the necessity for fairness, commercial efficiency, and tackling risks and all these traits are a vital part of the Data Science ecosystem.

Naked Statistics — Stripping the Dread from the Data

Naked Statistics by Charles Wheelan is an excellent introduction to statistics and how it gets used, misused and misrepresented. This book highlights the real-world application of statistics by stripping away the superficial arguments and revealing the underlying value of the subject.

Many compare the book to the ‘Stats 101 course’ without the math. So if you dread stats, this book tries to explain the intuition from basic probability to Central Limit theorem, from descriptive statistics to regression analysis, all in an easy and intuitive way, with a pinch of humour.


This book written by the visionary Hans Rosling (along with his son and daughter-in-law) is both inspiring and revelatory, filled with lively anecdotes and moving stories.

Hans Rosling uses data, statistics and succinct visualizations to give a different viewpoint of the world and its problems. It turns out that the world, for all its imperfections, is in a much better state than we might think. This book stresses the need to use facts to measure progress and development in the world to fight global ignorance.

The Data Science education focuses heavily on data wrangling and hypothesis testing. Hans Rosling through this book subtly reminds us that forming the wrong hypothesis is costly

The Signal and the Noise: Why So Many Predictions Fail-but Some Don’t

Nate Silver is a name which needs no introduction. He is a leading statistician, author and the founder of the award-winning website This book helps us to understand the limitations of predictions and areas where it can prove to be successful. Through his book, Nate takes us on a tour of the world of forecasting where much of data lies amongst the noise.

This is a helpful read if one is interested in getting to know how forecasting is done in the real world and how forecasters can overcome biases to uncover accurate and meaningful predictions.

Big Data: The Essential Guide to Work, Life and Learning in the Age of Insight

A lot of books have been written over the years on ‘Big Data’. However, the focus of this book is mainly on the applications of Big Data which are re-defining the businesses and processes around us.

The book has been written by Viktor Mayer-Schönberger and Kenneth Cukier, two of the world’s most respected data experts. They talk about what big data is, its benefits and how it can be utilized effectively. The examples and real-life experiences shared through this book are exemplary. This book not only highlights big data’s growing effect on just about everything ranging from business to government, from science to medicine but also impresses upon the Dark side of Big Data.

Overall, the book provides a strong introduction to the Big Data revolution and can be a good read for aspiring data scientists exploring the field.

I am glad that I was able to read these books and I hope you will also be benefitted by them. While reading a book will not turn you into a successful Data Scientist overnight, it will definitely give you a much better and broader perspective to see and analyse things. After all, it is our job to make sense out of data.

This article was originally published here

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