The Real Work of Data Science: Turning data into information, better decisions下载

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 数据科学家和必须从数据科学团队获得更多收益的领导者的基本指南 “经济学人”大胆地宣称，数据现在是“世界上最有价值的资源。”但是，正如Kenett和Redman所描述的那样，解锁这一价值需要远远超过技术卓越。数据科学的真实工作探索了解问题，处理质量问题，与决策者建立信任，将数据科学团队置于正确的组织点，以及帮助公司实现数据驱动。这项工作解释了一个优秀的数据科学家和一个伟大的数据科学家之间的差异，在一个创造边际贡献的团队和一个推动业务的团队之间，在一个从数据中获得一些价值的公司和一个数据真正是“最有价值的资源。“ “这两位作者是分析，数据管理和数据质量方面的世界级专家;他们比我们大多数人都知道的更多地忘记了这些主题。他们的书是务实的，可以理解的，并专注于真正重要的事情。如果你想以任何身份进行数据科学，你需要阅读它。“ -Thomas H. Davenport，巴布森学院杰出教授，麻省理工学院数字经济倡议研究员 “我喜欢你的书。这些章节解决了几代人面临统计数据的问题，更新以反映当今的问题，例如计算大数据。“ -Sir David Cox，纳菲尔德学院*长，牛津大学统计学教授 “数据科学对于竞争力，良好的*，正确的决策至关重要。但什么是数据科学？到目前为止，Kenett和Redman给出了我在任何地方看到的主题的最佳介绍。它们解决了制定正确问题，收集正确数据，进行正确分析，做出正确决策以及衡量决策的实际影响等关键问题。这本书应该成为统计学和计算机科学系，商学院，分析学院以及最重要的是所有业务经理的必读书。“ -一个。 Blanton Godfrey，约瑟夫D.摩尔杰出大学教授，北卡罗来纳州立大学威尔逊纺织学院