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E-raamat: Big Data and Business Analytics [Taylor & Francis e-raamat]

Edited by (Harrisburg University of Science and Technology, Pennsylvania, USA)
  • Formaat: 304 pages, 4 Tables, black and white; 46 Illustrations, black and white
  • Ilmumisaeg: 23-Apr-2013
  • Kirjastus: Auerbach
  • ISBN-13: 9780429099854
Teised raamatud teemal:
  • Taylor & Francis e-raamat
  • Hind: 92,31 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 131,88 €
  • Säästad 30%
  • Formaat: 304 pages, 4 Tables, black and white; 46 Illustrations, black and white
  • Ilmumisaeg: 23-Apr-2013
  • Kirjastus: Auerbach
  • ISBN-13: 9780429099854
Teised raamatud teemal:
Cybersecurity, emergency management, healthcare, finance, and transportation are just some of the domains constantly and rapidly generating data that a skilled analyst can spin into profit. Here data analysts explain how to understand and exploit organizational big data. Their topics include capitalizing on a growing marketing opportunity, the intrinsic value of data, unlocking the hidden potential in electronic health records, extracting useful information from multivariate temporal data, and using big data and analytics to unlock generosity. Annotation ©2013 Book News, Inc., Portland, OR (booknews.com)

"The chapters in this volume offer useful case studies, technical roadmaps, lessons learned, and a few prescriptions to ‘do this, avoid that.’"
—From the Foreword by Joe LaCugna, Ph.D., Enterprise Analytics and Business Intelligence, Starbucks Coffee Company

With the growing barrage of "big data," it becomes vitally important for organizations to make sense of this data and information in a timely and effective way. That’s where analytics come into play. Research shows that organizations that use business analytics to guide their decision making are more productive and experience higher returns on equity. Big Data and Business Analytics helps you quickly grasp the trends and techniques of big data and business analytics to make your organization more competitive.

Packed with case studies, this book assembles insights from some of the leading experts and organizations worldwide. Spanning industry, government, not-for-profit organizations, and academia, they share valuable perspectives on big data domains such as cybersecurity, marketing, emergency management, healthcare, finance, and transportation.

  • Understand the trends, potential, and challenges associated with big data and business analytics
  • Get an overview of machine learning, advanced statistical techniques, and other predictive analytics that can help you solve big data issues
  • Learn from VPs of Big Data/Insights & Analytics via case studies of Fortune 100 companies, government agencies, universities, and not-for-profits

Big data problems are complex. This book shows you how to go from being data-rich to insight-rich, improving your decision making and creating competitive advantage.

Foreword vii
Joe LaCugna
Preface xv
About the Editor xvii
Contributors xix
Chapter 1 Architecting the Enterprise via Big Data Analytics
1(20)
Joseph Betser
David Belanger
Chapter 2 Jack and the Big Data Beanstalk: Capitalizing on a Growing Marketing Opportunity
21(22)
Tim Suther
Bill Burkart
Jie Cheng
Chapter 3 Frontiers of Big Data Business Analytics: Patterns and Cases in Online Marketing
43(26)
Daqing Zhao
Chapter 4 The Intrinsic Value of Data
69(18)
Omer Trajman
Chapter 5 Finding Big Value in Big Data: Unlocking the Power of High-Performance Analytics
87(16)
Paul Kent
Radhika Kulkarni
Udo Sglavo
Chapter 6 Competitors, Intelligence, and Big Data
103(14)
G. Scott Erickson
Helen N. Rothberg
Chapter 7 Saving Lives with Big Data: Unlocking the Hidden Potential in Electronic Health Records
117(14)
Juergen Klenk
Yugal Sharma
Jeni Fan
Chapter 8 Innovation Patterns and Big Data
131(16)
Daniel Conway
Diego Klabjan
Chapter 9 Big Data at the U.S. Department of Transportation
147(6)
Daniel Pitton
Chapter 10 Putting Big Data at the Heart of the Decision-Making Process
153(18)
Ian Thomas
Chapter 11 Extracting Useful Information from Multivariate Temporal Data
171(20)
Artur Dubrawski
Chapter 12 Large-Scale Time-Series Forecasting
191(20)
Murray Stokely
Farzan Rohani
Eric Tassone
Chapter 13 Using Big Data and Analytics to Unlock Generosity
211(18)
Mike Bugembe
Chapter 14 The Use of Big Data in Healthcare
229(20)
Katherine Marconi
Matt Dobra
Charles Thompson
Chapter 15 Big Data: Structured and Unstructured
249(20)
Arun K. Majumdar
John F. Sowa
Index 269
Dr. Jay Liebowitz is the Orkand Endowed Chair of Management and Technology, the only endowed chair at the University of Maryland University College. He previously served as a full professor in the Carey Business School at Johns Hopkins University. He was ranked one of the top 10 knowledge management (KM) researchers/practitioners out of 11,000 worldwide and was ranked number two worldwide in KM strategy according to the January 2010 Journal of Knowledge Management. He is a prolific author, Fulbright Scholar, Computer Educator of the Year (IACIS), IEEE Executive Fellow, and the founder and editor-in-chief of Expert Systems with Applications: An International Journal.

His most recent books are:





Knowledge Management Handbook: Collaboration and Social Networking, Second Edition Beyond Knowledge Management: What Every Leader Should Know Knowledge Management in Public Health Knowledge Management and E-Learning Knowledge Retention: Strategies and Solutions