Big Data and Business Analytics
"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.
Author Jay Liebowitz recently had an article published in The World Financial Review.www.worldfinancialreview.com/?p=1904
Foreword; Joe LaCugna
Architecting the Enterprise via Big Data Analytics; Joseph Betser and David Belanger
Jack and the Big Data Beanstalk: Capitalizing on a Growing Marketing Opportunity; Tim Suther, Bill Burkart, and Jie Cheng
Frontiers of Big Data Business Analytics: Patterns and Cases in Online Marketing; Daqing Zhao
The Intrinsic Value of Data; Omer Trajman
Finding Big Value in Big Data: Unlocking the Power of High-Performance Analytics; Paul Kent, Radhika Kulkarni, and Udo Sglavo
Competitors, Intelligence, and Big Data; G. Scott Erickson and Helen N. Rothberg
Saving Lives with Big Data: Unlocking the Hidden Potential in Electronic Health Records; Juergen Klenk, Yugal Sharma, and Jeni Fan
Innovation Patterns and Big Data; Daniel Conway and Diego Klabjan
Big Data at the U.S. Department of Transportation; Daniel Pitton
Putting Big Data at the Heart of the Decision-Making Process; Ian Thomas
Extracting Useful Information from Multivariate Temporal Data; Artur Dubrawski
Large-Scale Time-Series Forecasting; Murray Stokely, Farzan Rohani, and Eric Tassone
Using Big Data and Analytics to Unlock Generosity; Mike Bugembe
The Use of Big Data in Healthcare; Katherine Marconi, Matt Dobra, and Charles Thompson
Big Data: Structured and Unstructured; Arun Majumdar and John Sowa
"The promise and potential of big data and smart analysis are realized in better decisions and stronger business results. But good ideas rarely implement themselves, and often the heavy hand of history means that bad practices and outdated processes tend to persist. Even in organizations that pride themselves on having a vibrant marketplace of ideas, converting data and insights into better business outcomes is a pressing and strategic challenge for senior executives. ... 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