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Big Data at Work: Dispelling the Myths, Uncovering the Opportunities Hardcover – Illustrated, 25 Feb. 2014
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Thomas H. Davenport
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When the term big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind.
Now, in clear, conversational language, Davenport explains what big data meansand why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold.
This book will help you understand:
Why big data is important to you and your organization
What technology you need to manage it
How big data could change your job, your company, and your industry
How to hire, rent, or develop the kinds of people who make big data work
The key success factors in implementing any big data project
How big data is leading to a new approach to managing analytics
With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunitiesfrom improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.
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Print length240 pages
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LanguageEnglish
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PublisherHarvard Business Review Press
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Publication date25 Feb. 2014
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Dimensions15.75 x 2.29 x 23.37 cm
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ISBN-101422168166
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ISBN-13978-1422168165
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Review
Davenport has written a thought-provoking book about a current topic that is becoming more important to business and individuals every day. Summed up: Highly recommended.” Choice magazine
The book covers all aspects of the issue, from what big data means, to whom you must hire, to what technologies to follow. It’s surprisingly easy to read, given the topic, and offers good examples to ponder from startups and large firm.” Globe & Mail
Davenport is a methodologically-sound researcher. His deep interviews and surveys of executives and data scientists set a standard for excellence in an industry where marketing bravado generally supersedes scientific rigor” Information Management (information-management.com)
ADVANCE PRAISE for Big Data at Work:
Jane Griffin, Managing Director Analytics, Deloitte Canada and Americas
Big Data at Work is the first and only book to describe how real organizations are using big data, extracting value from it, and combining it with other forms of data and analytics. It’s an invaluable guide to planning and action.”
Jonathan D. Becher, Chief Marketing Officer, SAP
Is Big Data a buzzword or does it have practical applications in business? Big Data at Work goes beyond tech-talk to help businesspeople turn Big Data into Big Decisions.”
Gary L. Gottlieb, MD, MBA, President and CEO, Partners HealthCare System, Inc.; Professor of Psychiatry, Harvard Medical School
Big Data at Work provides a terrific foundation for thoughtful planning to exploit the business opportunities created by diverse and vast sources of information. Davenport’s clear approach will enlighten managers about the need to carefully mine these resources to improve operations and products while driving new and competitive strategies.”
Rob Bearden, CEO, Hortonworks
Thomas Davenport has supplied a smart, practical book for anyone looking to unlock the opportunitiesand avoid the pitfallsof big data.”
Adele K. Sweetwood, Vice President, Americas Marketing & Support, SAS
Conversational, engaging, and an exceptional guide for decision making in the big data world. Big Data at Work offers insight to the business and technology components of a big data strategy, a path to success, and best practices from across industry sectors.”
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Product details
- Publisher : Harvard Business Review Press; Illustrated edition (25 Feb. 2014)
- Language : English
- Hardcover : 240 pages
- ISBN-10 : 1422168166
- ISBN-13 : 978-1422168165
- Dimensions : 15.75 x 2.29 x 23.37 cm
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Best Sellers Rank:
849,927 in Books (See Top 100 in Books)
- 612 in Information Management
- 2,398 in Strategy Management
- 2,540 in Business Decision Making Skills
- Customer reviews:
About the author

Tom Davenport is the President's Distinguished Professor of Information Technology and Management at Babson College. He has led research centers at Accenture, McKinsey and Company, Ernst & Young, and CSC Index, and has taught at Harvard Business School, Dartmouth's Tuck School, the University of Texas, and the University of Chicago. He is a widely published author and speaker on the topics of analytics, information and knowledge management, reengineering, enterprise systems, and electronic business. Tom's latest book--coauthored with Jeanne Harris--is Competing on Analytics: The New Science of Winning, a best-seller that has been translated into 13 languages. Prior to this, Tom wrote, co-authored or edited twelve other books, including the first books on business process reengineering, knowledge management, attention management, and enterprise systems. He has written over 100 articles for such publications as Harvard Business Review, Sloan Management Review, California Management Review, the Financial Times, and many other publications, and has been a columnist for Information Week, CIO, and Darwin magazines. In 2003 he was named one of the world's top 25 consultants by Consulting magazine, and in 2007 and 8 was named one of the 100 most influential people in the IT industry by Ziff-Davis magazines. His blog for Harvard Business Online is http://discussionleader.hbsp.com/davenport/
Customer reviews
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I think this may be a good book for senior managers who want to learn a few big data concepts.
There are several good books available about Big Data - this is one of them.
I agree with him: "Big data is here to stay and of substantial importance to many organizations. [Therefore] organizations and managers ignore it at their peril." It is also true that a number of myths about big data have developed, in part because of confusion about the term. As Davenport explains, "First, there is the issue that [begin italics] big [end italics] is only one aspect of what's distinctive about new forms of data, and for many organizations, it's not the most important characteristic...The term [begin italics] big [end italics] is obviously relative -- what's big today won't be so large tomorrow [and] what's big to one organization is small to another...but the only real way in which 'size matters' with data is in the amount of hardware you will have to buy to store and process it...One other problem is that too many people- -- and vendors in particular -- are already using [begin italics] big data [end italics] to mean any analytics or in extreme cases even reporting and conventional business intelligence."
What to do...and what NOT to do? Davenport answers these in the book. In discussions with countless senior-level executives about what is often referred to as "Big Data," I sense that most (if not all) of them are convinced of its potential importance but defer almost entirely to others (quants) to answer the two questions. Davenport is quite correct when stressing that there are business decisions -- not big data decisions -- to be made at the highest level, in collaboration with those who will be primarily responsible for the installation and maintenance of the systems needed. Moreover, those systems will be most effective and most efficient only if those who generate the data (whatever the data's nature and extent may be) understand the needs to be served and the strategic objectives to be achieved. There must be an action plan for managers. Davenport includes a set of questions at the conclusion of each chapter. The answers to those questions will guide and inform the design and implementation of that plan.
In this context, I am again reminded of a passage in Judgment Calls, when Davenport and Manville offer "an antidote for the Great Man theory of decision making and organizational performance": [begin italics] organizational judgment [end italics]. That is, "the collective capacity to make good calls and wise moves when the need for them exceeds the scope of any single leader's direct control." Those involved with the action plan for managers need to keep that passage in mind.
These are among the dozens of business subjects and issues of special interest and value to me, also listed to indicate the scope of Davenport's coverage.
o Beyond the Big Data Hype (Pages 2-5)
o Deconstructing the Term Big Data (6-9)
o What's New from a Management Perspective? (15-18)
o The New Opportunities from Big Data (22-26)
o Big Data and Key Business Functions (50-56)
o What's Your Big Data Objective? (60-70)
o How Rapidly to Move Out? (79-84)
o The Team Approach (99-101)
o Retention of Data Scientists (104-106)
o What's Really New About Big Data Technology? (115-118)
o The Big Data Stack (119-126)
o Other Factors to Consider in Big Data Success (146-151)
o Lessons from Big Data Start-Ups and Online Firms (154-167)
o Lessons Not Learned by Start-Ups and Online Firms (167-172)
o Integrating Organizational Structures and Skills (182-185)
o The Rise of Analytics 3.0 (194-203)
No brief commentary such as mine can do full justice to the wealth of material that Thomas Davenport provides. However, I hope I have at least indicated why I think so highly of him and of his contributions knowledge leadership. Here is how he concludes his latest and, in my opinion, his most important book thus far: The primary value from big data "comes not from the data in its raw form (no matter how big it is) but from the processing and analysis of it and the insights, products, and services that emerge from analysis. The sweeping changes in big data technologies and management approaches need to be accompanied by similarly dramatic shifts in how data supports decisions and product/service innovation. There is little doubt that analytics can transform organizations and the firms that lead the 3.0 charge will seize the most value."
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How prepared is your organization to embark on big data projects?
Check out the "Big Data Readiness Assessment Survey" in the Appendix (Pages 205-209). It is based on the DELTA model described in Chapter 6 (Pages 135-136). The acronym refers to data, enterprise, leadership, targets, and analysts.





