Getting Started with Data Science: Storytelling with Data

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Earlier this month, IBM Press and Pearson have published my book titled: Getting Started with Data Science: Making Sense of Data with Analytics. You can download sample pages, including a complete chapter. There are 104 pages in the sample. You can also watch a brief interview about the book recorded earlier at the IBM Insight2015 Conference.

The very purpose of authoring this book was to rethink the way we have been teaching statistics and analytics to students and practitioners. It is no secret that most students required to take the mandatory stats course dislike it. I believe it has something to do with the way we have been teaching the subject than to do with the aptitude of our students. Furthermore, I believe there is a greater opportunity to equip the students with the skills needed in a world awash with data where competing on analytics defines the real competitive advantage.

No wonder, the latest issue of the leading publication on the subject, The American Statistician, is dedicated to reimagining how statistics should be taught in the undergraduate curriculum. The editors noted:
“We hope that this collection of articles as well as the online discussion provide useful fodder for further review, assessment, and continuous improvement of the undergraduate statistics curriculum that will allow the next generation to take a leadership role by making decisions using data in the increasingly complex world that they will inhabit.”
I am confident that my book will do its small part in equipping the next generation of students with the kind of skills needed to succeed in a data-centric world. For one, I have taken a storytelling approach to statistics. This book reinforces the point that data science and analytics training should be applied rather than theoretical, and the ultimate purpose of producing or consuming statistical analysis is to tell fascinating stories from it. Therefore, the book opens with the chapter titled, The Bazaar of Storytellers.

Who is this book for?

While the world is awash with large volumes of data, inexpensive computing power, and vast amounts of digital storage, the skilled workforce capable of analyzing data and interpreting it is in short supply. A 2011 McKinsey Global Institute report suggests that “the United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data.”

Getting Started with Data Science (GSDS) is a purpose-written book targeted at those professionals who are tasked with analytics, but they do not have the comfort level needed to be proficient in data-driven analytics. GSDS appeals to those students who are frustrated with the impractical nature of the prescribed textbooks and are looking for an affordable text to serve as a long-term reference. GSDS embraces the 24-7 streaming of data and is structured for those users who have access to data and software of their choice, but do not know what methods to use, how to interpret the results, and most importantly how to communicate findings as reports and presentations in print or on-line.

GSDS is a resource for millions employed in knowledge-driven industries where workers are increasingly expected to facilitate smart decision-making using up-to-date information that sometimes takes the form of continuously updating data.

At the same time, the learning-by-doing approach in the book is equally suited for independent study by senior undergraduate and graduate students who are expected to conduct independent research for their coursework or dissertations.

Praise for the book

I am also pleased to share with you the praise for my book by Dr. Munir Sheikh, Canada’s former chief statistician:
“The power of data, evidence, and analytics in improving decision-making for individuals, businesses, and governments is well known and well documented. However, there is a huge gap in the availability of material for those who should use data, evidence, and analytics but do not know how. This fascinating book plugs this gap, and I highly recommend it to those who know this field and those who want to learn.”
— Munir A. Sheikh, Ph.D., Distinguished Fellow and Adjunct Professor at Queen’s University

Tom Davenport, author of the bestselling books Competing on Analytics and Big Data @ Work.has the following to say about my book:
“A coauthor and I once wrote that data scientists held ‘the sexiest job of the 21st century.’ This was not because of their inherent sex appeal, but because of their scarcity and value to organizations. This book may reduce the scarcity of data scientists, but it will certainly increase their value. It teaches many things, but most importantly it teaches how to tell a story with data.”
—Thomas H. Davenport, Distinguished Professor, Babson College; Research Fellow, MIT.

Dr. Patrick Surry
, Chief Data Scientist at had the following to say:
“This book addresses the key challenge facing data science today, that of bridging the gap between analytics and business value. Too many writers dive immediately into the details of specific statistical methods or technologies, without focusing on this bigger picture. In contrast, Haider identifies the central role of narrative in delivering real value from big data.

“The successful data scientist has the ability to translate between business goals and statistical approaches, identify appropriate deliverables, and communicate them in a compelling and comprehensible way that drives meaningful action. To paraphrase Tukey, ‘Far better an approximate answer to the right question, than an exact answer to a wrong one.’ Haider’s book never loses sight of this central tenet and uses many realworld examples to guide the reader through the broad range of skills, techniques, and tools needed to succeed in practical data-science. “Highly recommended to anyone looking to get started or broaden their skillset in this fast-growing field.”
And finally, Professor Atif Mian, author of the best-selling book: The House of Debt offered the following assessment:
“We have produced more data in the last two years than all of human history combined. Whether you are in business, government, academia, or journalism, the future belongs to those who can analyze these data intelligently. This book is a superb introduction to data analytics, a must-read for anyone contemplating how to integrate big data into their everyday decision making.”
— Professor Atif Mian, Theodore A. Wells ’29 Professor of Economics and Public Affairs,
Princeton University; Director of the Julis-Rabinowitz Center for Public Policy and Finance at the Woodrow Wilson School.

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