The Real Work of Data Science: Turning Data Into Information, Better Decisions, and Stronger Organizations

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

《真正的資料科學工作》是一本針對資料科學家和領導者的必讀指南。《經濟學人》大膽聲稱數據現在是「世界上最有價值的資源」。但是，正如Kenett和Redman所描述的那樣，要發掘這個價值需要遠遠超出技術卓越的範疇。《真正的資料科學工作》探討了理解問題、處理質量問題、與決策者建立信任、將資料科學團隊放在正確的組織位置以及幫助公司實現數據驅動等方面。這些工作決定了一個優秀資料科學家和一個出色資料科學團隊的區別，決定了一家公司是否能從數據中獲得價值，以及數據是否真正成為「最有價值的資源」。

「這兩位作者是分析、資料管理和資料質量方面的世界級專家；他們對這些主題的了解遠遠超過我們大多數人。他們的書實用、易懂，並且專注於真正重要的事情。如果你想以任何形式從事資料科學，你需要閱讀這本書。」
--Thomas H. Davenport，巴布森學院傑出教授，麻省理工學院數字經濟倡議計劃研究員

「我喜歡你們的書。這些章節解決了統計學家幾代人面臨的問題，並更新以反映當今的問題，例如計算大數據。」
--Sir David Cox，努菲爾德學院院長，牛津大學統計學教授

「資料科學對於競爭力、良好的政府和正確的決策至關重要。但是，什麼是資料科學？Kenett和Redman提供了迄今為止最好的介紹。他們解答了制定正確問題、收集正確資料、進行正確分析、做出正確決策以及衡量決策實際影響的關鍵問題。這本書應該成為統計學和計算機科學系、商學院、分析研究所以及所有商業經理人的必讀之作。」
--A. Blanton Godfrey，北卡羅來納州立大學威爾遜紡織學院約瑟夫·D·摩爾傑出大學教授

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.

RON S. KENETT 是以色列 KPA Group 的主席，以及以色列海法 Technion 的高級研究員，曾任紐約州 Binghamton 的紐約州立大學的運營管理教授，並擔任歐洲商業和工業統計網絡的主席。

THOMAS C. REDMAN，被稱為「數據專家」，是數據質量解決方案公司的總裁。他幫助領導者和公司了解他們在數據方面最重要的問題和機遇，制定方向，並建立組織能力以實施。