Big Data, Mining, and Analytics

Stephan Kudyba has developed computerized models for trading financial markets in the investment banking industry and has provided Business Intelligence based solutions involving data mining applications for organizations across industry sectors. He has published numerous books and articles, has been interviewed by prominent magazines and speaks at corporate and academic events addressing data, information and knowledge management and organizational performance.Dr. Kudyba is a professor in the school of management at New Jersey Institute of Technology where he teaches business courses addressing data, information and knowledge management, market research and internet marketing. He has held editorial positions for academic journals, is a member of a number of information management based societies, and maintains relations with organizations in a variety of industries addressing strategic initiatives.

Kudyba again has put together an all-star cast in his new book focused on leveraging data, including the more traditional structured and also the unstructured incomprehensible source, to generate actionable information. This most current book provides a framework for both the advanced data jockeys to more analytically focused data-driven decision makers. A must-read for those wishing to be on the cutting edge of leveraging the multitude of data sources that businesses capture today.—Jeff Nicola, VP of Retail Sales at one of the nation's largest health insurance firms, and a Six Sigma Black BeltDr. Kudyba has drawn upon his own, as well as industry experts’, experiences to create a timely and thought provoking book on business intelligence. Big Data, Mining, and Analytics: Components of Strategic Decision Making should be recommended reading for both industry professionals and students involved in the challenge of developing actionable information. As described in this book, it is not a situation of the lack of data. It is, however, a situation where the plethora of amounts and types of data (whether structured or not) provides an arguably evolutionary situation, replete with new challenges, opportunities, and pitfalls. I highly recommend this book to anyone involved or interested in how big data, data mining, and analytics fit together in our current state; a state where the complexity, amount, and inadequate methodologies threaten the opportunities presented to leverage new sources of information to improve strategic as well as operational decision making.—Thad Perry, Ph.D., Director of Healthcare Informatics, Tennessee Technological UniversityJust as early analytical competitors in the ‘small data’ era moved out ahead of their competitors and built a sizable competitive edge, the time is now for firms to seize the big data opportunity. ... an excellent review of the opportunities involved in this revolution ... The road to the Big Data Emerald City is paved with many potholes. Reading this book can help you avoid many of them, and avoid surprise when your trip is still a bit bumpy.—From the Foreword by Thomas H. Davenport, Distinguished Professor, Babson College; Fellow, MIT Center for Digital Business; and Co-Founder, International Institute for Analytics

• Introduction to the Big Data Era. Information Creation through Analytics. Big Data Analytics-Architectures, Implementation. Methodology, and Tools. Data Mining Methods and the Rise of Big Data. Data Management and Model Creation Process of Structured Data for Mining and Analytics. The Internet: A Source of New Data for Mining in Marketing. Mining and Analytics in E-Commerce. Streaming Data in the Age of Big Data. Using CEP for Real-Time Data Mining. Transforming Unstructured Data into Useful Information. Mining Big Textual Data. The New Medical Frontier: Real-Time Wireless Medical Data Acquisition for 21st-Century Healthcare and Data Mining Challenges.