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Thursday, April 25, 2019

Big Data and Business Analytics


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Description
So why Big Data and Business Analytics? Is it that the White House Office of Science and Technology Policy held a conference on March 29, 2012, citing that $200 million is being awarded for research and development on big data and associated analytics? Is it that, according to KMWorld, big data revenue will grow from $5 billion in 2011 to $50 billion in 2017? Or is it just that we are entrenched in the three Vs: volume of data, variety of data, and the velocity of data?

With the barrage of data from such domains as cybersecurity, emergency management, healthcare, finance, transportation, and other domains, it becomes vitally important for organizations to make sense of this data and information on a timely and effective basis to improve the decisionmaking process. That’s where analytics come into play. Studies have shown that by 2018, there will be a shortage of 140,000 to 190,000 business data analysts in the United States alone. These analysts should know machine learning, advanced statistical techniques, and other predictive analytics to make sense of the various types of data—structured, unstructured, text, numbers, images, and others.

Content:-
Foreword
Preface
About the Editor
Contributors
Chapter 1: Architecting the Enterprise via Big Data Analytics
Chapter 2: Jack and the Big Data Beanstalk: Capitalizing on a Growing Marketing Opportunity
Chapter 3: Frontiers of Big Data Business Analytics: Patterns and Cases in Online Marketing
Chapter 4: The Intrinsic Value of Data
Chapter 5: Finding Big Value in Big Data: Unlocking the Power of High-Performance Analytics.
Chapter 6: Competitors, Intelligence, and Big Data
Chapter 7: Saving Lives with Big Data: Unlocking the Hidden Potential in Electronic Health Records
Chapter 8: Innovation Patterns and Big Data
Chapter 9: Big Data at the U.S. Department of Transportation
Chapter 10: Putting Big Data at the Heart of the Decision-Making Process
Chapter 11: Extracting Useful Information from Multivariate Temporal Data.
Chapter 12: Large-Scale Time-Series Forecasting
Chapter 13: Using Big Data and Analytics to Unlock Generosity
Chapter 14: The Use of Big Data in Healthcare
Chapter 15: Big Data: Structured and Unstructured

Author Details
"Dr. Jay Liebowitz" is the Orkand Endowed Chair of Management and Technology in the Graduate School at the University of Maryland University College (UMUC). He previously served as a professor in the Carey Business School at Johns Hopkins University.




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