Research Catalog

Big data, mining, and analytics : components of strategic decision making

Title
Big data, mining, and analytics : components of strategic decision making / Stephan Kudyba ; foreword by Thomas H. Davenport.
Publication
Boca Raton : Taylor & Francis, [2014]

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TextRequest in advance HD30.28 .B544 2014Off-site

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Additional Authors
Kudyba, Stephan, 1963-
Description
xv, 305 pages : illustrations (some color); 25 cm
Summary
"Foreword Big data and analytics promise to change virtually every industry and business function over the next decade. Any organization that gets started early with big data can gain a significant competitive edge. Just as early analytical competitors in the "small data" era (including Capital One bank, Progressive Insurance, and Marriott hotels) moved out ahead of their competitors and built a sizable competitive edge, the time is now for firms to seize the big data opportunity. As this book describes, the potential of big data is enabled by ubiquitous computing and data gathering devices; sensors and microprocessors will soon be everywhere. Virtually every mechanical or electronic device can leave a trail that describes its performance, location, or state. These devices, and the people who use them, communicate through the Internet--which leads to another vast data source. When all these bits are combined with those from other media--wireless and wired telephony, cable, satellite, and so forth--the future of data appears even bigger. The availability of all this data means that virtually every business or organizational activity can be viewed as a big data problem or initiative. Manufacturing, in which most machines already have one or more microprocessors, is increasingly a big data environment. Consumer marketing, with myriad customer touchpoints and clickstreams, is already a big data problem. Google has even described its self-driving car as a big data project. Big data is undeniably a big deal, but it needs to be put in context"--
Subject
  • Strategic planning > Data processing
  • Data mining
  • Big data
  • Business planning > Data processing
  • Webometrics
  • Data loggers
  • COMPUTERS / Database Management / General
  • COMPUTERS / Database Management / Data Mining
  • COMPUTERS / Information Technology
Bibliography (note)
  • Includes bibliographical references and index.
ISBN
  • 9781466568709 (hardback)
  • 1466568704 (hardback)
LCCN
  • 2013049469
  • 99958341454
OCLC
  • ocn796749848
  • 796749848
  • SCSB-13567483
Owning Institutions
Columbia University Libraries