The best type of analytics books are ones that don’t just tell you how this industry works but helps you perform your daily roles effectively. They don’t just explain the nuances of data science or how to conduct analysis but teach you the art of storytelling.

If you want to position yourself as a digital transformation advocate, these books will show you ways to decode the art of transforming your business digitally. They will also make you become a better analytics professional, whether you are a newbie or have been in the industry for decades.

Here’s selection of the

5 Bestselling Big Data Analytics and Data Science Books

Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic



Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation.



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Data Analytics Made Accessible by Anil Maheshwari



This book fills the need for a concise and conversational book on the growing field of Data Science. Easy to read and informative, this lucid book covers everything important, with concrete examples, and invites the reader to join this field. The chapters in the book are organized for a typical one-semester course. The book contains case-lets from real-world stories at the beginning of every chapter. There is also a running case study across the chapters as exercises. This book is designed to provide a student with the intuition behind this evolving area, along with a solid toolset of the major data mining techniques and platforms. Finally, it includes a tutorial for R platform.



The 2018 edition includes a new chapter on Artificial Intelligence primer.



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Ten Signs of Data Science Maturity by Peter Guerra and Kirk Borne



If you are a data science leader looking for answers to these questions, you should grab this book today. The book has a detailed report that provides a brief discussion of each of the ten signs of data science maturity. It encourages analytics professionals to give members of the organization access to all the available data, use agile, and leverage “DataOps” – DevOps for data product development, help your data science team sharpen its skills through open or internal competitions, and personify data science as a way of doing things, not a thing to do.



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Too Big to Ignore: The Business Case for Big Data (Wiley and SAS Business Series) by Phil Simon



Too Big to Ignore explains why Big Data is a big deal. Simon provides commonsense, jargon-free advice for people and organizations looking to understand and leverage Big Data. Rife with case studies, examples, analysis, and quotes from real-world Big Data practitioners, the book is required reading for chief executives, company owners, industry leaders, and business professionals.



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Weapons of Math Destruction by Cathy O’Neil



“O’Neil’s book offers a frightening look at how algorithms are increasingly regulating people… Her knowledge of the power and risks of mathematical models, coupled with a gift for analogy, makes her one of the most valuable observers of the continuing weaponization of big data… [She] does a masterly job explaining the pervasiveness and risks of the algorithms that regulate our lives.”

—New York Times Book Review



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Recommended reading: 5 Variations of Artificial Intelligence