E-Book Content
Praise for The Real Work of Data Science 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 I am already in love with your book based on the overview and preface!! What a creative approach! Speaks a lot to your ability to tell a good story – one of the key ways of reasoning for a good data scientist! Hollylynne S. Lee Professor, Mathematics and Statistics Education and Faculty Fellow, Friday Institute for Educational Innovation, North Carolina State University The root causes of business failures typically are management, not technology. In today’s complex and changing digital world, the advice in The Real Work of Data Science is essential. Read it and do it. John A. Zachman Chairman – Zachman International and Executive Director – FEAC Institute If you are wondering what the real challenges and solutions to solving your ‘Big Data’ problem are, this is a must read book. Ron and Tom move past the technology hype and highlight the real issues and opportunities in leveraging data science to the benefit of your organization Jeff MacMillan Chief Analytics and Data Officer, Morgan Stanley Wealth Management
Much needed! Neil Lawrence Professor of Machine Learning at the University of Sheffield and Machine Learning team manager at Amazon More than 80% of data science projects fail, either partially or wholly, at the implementation stage. There is a wealth of books on the technical and mechanical aspects of data science, but little to guide data scientists and managers on the holistic integration of data science into organizations in a way that produces success. This well-written book fills that gap. Peter Bruce Founder and Chief Academic Officer, The Institute for Statistics Education C’est livre est très intéressant et plein de très bonnes choses intelligentes et utiles. Il sera sans nul doute très précieux. Jean Michel Poggi Professor of Statistics at Paris-Descartes University and Mathematics Laboratory, Orsay University, Paris, France, Past President of the Société Française de Statistique and Vice-President of the Federation of European National Statistical Societies I like the very direct and succinct style. You are certainly right on target when you say you can’t stress enough the importance of understanding the real problem. Other of your points in Chapter 1 really hit home, such as data scientists spending more time on data quality than on analysis. (I’m glad they do.) Further, you are absolutely correct that data scientists must translate their results into the language of the decision-maker. I also recognize the liberal use of anecdotes in the book. For instance, the remarks about Bill Hunter, the ice cream sales, the Pokémon experiment, etc. I personally like this, and I do this in all of my speeches since I think it really hooks the audience. Barry Nussbaum Past Chief Statistician, the United States Environmental Protection Agency and Past President of the American Statistical Association I think this book is excellent for an introductory course in data science. It could be used with students at university level or with professionals in specialist courses. Luciana Dalla Valle Lecturer in Statistics and Programme Manager of the MSc Data Science and Business Analytics, School of Computing, Electronics and Mathematics, Plymouth Univers