Data-Science-for-Business.pdf

Data Science for Business is intended for several sorts of readers: • Business people who will be working with data scientists, managing data science– oriented projects, or investing in data science ventures, • Developers who will be implementing data science solutions, and • Aspiring data scientists. This is not a book about algorithms, nor is it a replacement for a book about algorithms. We deliberately avoided an algorithm-centered approach. We believe there is a relatively small set of fundamental concepts or principles that underlie techniques for extracting useful knowledge from data. These concepts serve as the foundation for many wellknown algorithms of data mining. Moreover, these concepts underlie the analysis of data-centered business problems, the creation and evaluation of data science solutions, and the evaluation of general data science strategies and proposals. Accordingly, we organized the exposition around these general principles rather than around specific algorithms. Where necessary to describe procedural details, we use a combination of text and diagrams, which we think are more accessible than a listing of detailed algorithmic steps. Review, 'A must-read resource for anyone who is serious about embracing the opportunity of big data.', -- Craig Vaughan, Global Vice President at SAP, 'This book goes beyond data analytics 101. It's the essential guide for those of us (all of us?) whose businesses are built on the ubiquity of data opportunities and the new mandate for data-driven decision-making.', --Tom Phillips, CEO of Media6Degrees and Former Head of Google Search and Analytics, 'Data is the foundation of new waves of productivity growth, innovation, and richer customer insight. Only recently viewed broadly as a source of competitive advantage, dealing well with data is rapidly becoming table stakes to stay in the game. The authors' deep applied experience makes this a must read--a window into your competitor's strategy.', -- Alan Murray, Serial Entrepreneur; Partner at Coriolis Ventures, 'This timely book says out loud what has finally become apparent: in the modern world, Data is Business, and you can no longer think business without thinking data. Read this book and you will understand the Science behind thinking data.', -- Ron Bekkerman, Chief Data Officer at Carmel Ventures, 'A great book for business managers who lead or interact with data scientists, who wish to better understand the principles and algorithms available without the technical details of single-disciplinary books.', -- Ronny Kohavi, Partner Architect at Microsoft Online Services Division, About the Author, Foster Provost is Professor and NEC Faculty Fellow at the NYU Stern School of Business where he teaches in the MBA, Business Analytics, and Data Science programs. His award-winning research is read and cited broadly. Prof. Provost has co-founded several successful companies focusing on data science for marketing., Tom Fawcett holds a Ph.D. in machine learning and has worked in industry R&D for more than two decades for companies such as GTE Laboratories, NYNEX/Verizon Labs, and HP Labs. His published work has become standard reading in data science. underlie techniques for extracting useful knowledge from data. These concepts serve as the foundation for many wellknown algorithms of data mining. Moreover, these concepts underlie the analysis of data-centered business problems, the creation and evaluation of data science solutions, and the evaluation of general data science strategies and proposals. Accordingly, we organized the exposition around these general principles rather than around specific algorithms. Where necessary to describe procedural details, we use a combination of text and diagrams, which we think are more accessible than a listing of detailed algorithmic steps. Review, 'A must-read resource for anyone who is serious about embracing the opportunity of big data.', -- Craig Vaughan, Global Vice President at SAP, 'This book goes beyond data analytics 101. It's the essential guide for those of us (all of us?) whose businesses are built on the ubiquity of data opportunities and the new mandate for data-driven decision-making.', --Tom Phillips, CEO of Media6Degrees and Former Head of Google Search and Analytics, 'Data is the foundation of new waves of productivity growth, innovation, and richer customer insight. Only recently viewed broadly as a source of competitive advantage, dealing well with data is rapidly becoming table stakes to stay in the game. The authors' deep applied experience makes this a must read--a window into your competitor's strategy.', -- Alan Murray, Serial Entrepreneur; Partner at Coriolis Ventures, 'This timely book says out loud what has finally become apparent: in the modern world, Data is Business, and you can no longer think business without thinking data. Read this book and you will understand the Science behind thinking data.', -- Ron Bekkerman, Chief Data Officer at Carmel Ventures, 'A great book for business managers who lead or interact with data scientists, who wish to better understand the principles and algorithms available without the technical details of single-disciplinary books.', -- Ronny Kohavi, Partner Architect at Microsoft Online Services Division, About the Author, Foster Provost is Professor and NEC Faculty Fellow at the NYU Stern School of Business where he teaches in the MBA, Business Analytics, and Data Science programs. His award-winning research is read and cited broadly. Prof. Provost has co-founded several successful companies focusing on data science for marketing., Tom Fawcett holds a Ph.D. in machine learning and has worked in industry R&D for more than two decades for companies such as GTE Laboratories, NYNEX/Verizon Labs, and HP Labs. His published work has become standard reading in data science.