The Real Work of Data Science - by Ron S Kenett & Thomas C Redman (Paperback)

About the Book

"The essential guide for data scientists and for leaders who must get more from their data science teams. The Economist boldly claims that data are now 'the world's most valuable resource.' But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. Individual data scientists must fully extend themselves. They must make sure they understand the real problems their companies and agencies face, they must build trust with decision-makers, deal with quality issues, help decision makers become more demanding customers of data science, and they must teach their colleagues how to understand and interpret data science--even conduct basic analyses themselves. Further up in the management chain, managers of data science teams must help senior leaders understand where data and data science fit, ensure their teams are placed in the right spots organizationally, and put in place programs that help the entire organization become data-driven. This Kenett and Redman claim, is the 'real work of data science.' And it is this work that will spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is 'the most valuable resource'"--

Book Synopsis

The essential guide for data scientists and for leaders who must get more from their data science teams

The Economist boldly claims that data are now "the world's most valuable resource." But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. The Real Work of Data Science explores understanding the problems, dealing with quality issues, building trust with decision makers, putting data science teams in the right organizational spots, and helping companies become data-driven. This is the work that spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is "the most valuable resource."

"These two authors are world-class experts on analytics, data management, and data quality; they've forgotten more about these topics than most of us will ever know. Their book is pragmatic, understandable, and focused on what really counts. If you want to do data science in any capacity, you need to read it."
--Thomas H. Davenport, Distinguished Professor, Babson College and Fellow, MIT Initiative on the Digital Economy

"I like your book. The chapters address problems that have faced statisticians for generations, updated to reflect today's issues, such as computational Big Data."
--Sir David Cox, Warden of Nuffield College and Professor of Statistics, Oxford University

"Data science is critical for competitiveness, for good government, for correct decisions. But what is data science? Kenett and Redman give, by far, the best introduction to the subject I have seen anywhere. They address the critical questions of formulating the right problem, collecting the right data, doing the right analyses, making the right decisions, and measuring the actual impact of the decisions. This book should become required reading in statistics and computer science departments, business schools, analytics institutes and, most importantly, by all business managers."
--A. Blanton Godfrey, Joseph D. Moore Distinguished University Professor, Wilson College of Textiles, North Carolina State University

From the Back Cover

The essential guide for data scientists and for leaders who must get more from their data science teams

The Economist boldly claims that data are now "the world's most valuable resource." But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. The Real Work of Data Science explores understanding the problems, dealing with quality issues, building trust with decision makers, putting data science teams in the right organizational spots, and helping companies become data-driven. This is the work that spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is "the most valuable resource."

"These two authors are world-class experts on analytics, data management, and data quality; they've forgotten more about these topics than most of us will ever know. Their book is pragmatic, understandable, and focused on what really counts. If you want to do data science in any capacity, you need to read it."
--Thomas H. Davenport, Distinguished Professor, Babson College and Fellow, MIT Initiative on the Digital Economy

"I like your book. The chapters address problems that have faced statisticians for generations, updated to reflect today's issues, such as computational Big Data."
--Sir David Cox, Warden of Nuffield College and Professor of Statistics, Oxford University

"Data science is critical for competitiveness, for good government, for correct decisions. But what is data science? Kenett and Redman give, by far, the best introduction to the subject I have seen anywhere. They address the critical questions of formulating the right problem, collecting the right data, doing the right analyses, making the right decisions, and measuring the actual impact of the decisions. This book should become required reading in statistics and computer science departments, business schools, analytics institutes and, most importantly, by all business managers."
--A. Blanton Godfrey, Joseph D. Moore Distinguished University Professor, Wilson College of Textiles, North Carolina State University

About the Author

RON S. KENETT is Chairman of the KPA Group, Israel, Senior Research Fellow at the Samuel Neaman Institute, Technion, Haifa and, previously, Professor of Operations Management, State University of New York, Binghamton, New York and President of the European Network for Business and Industrial Statistics.

THOMAS C. REDMAN, "the Data Doc," is the President of Data Quality Solutions. He helps leaders and companies understand their most important issues and opportunities in the data, chart a course, and build the organizational capabilities they need to execute.