There is an ongoing data explosion transpiring that will make previous creations, collections, and storage of data look trivial. Big Data, Mining, and Analytics: Components of Strategic Decision Making ties together big data, data mining, and analytics to explain how readers can leverage them to extract valuable insights from their data. Facilitating a clear understanding of big data, it supplies authoritative insights from expert contributors into leveraging data resources, including big data, to improve decision making.
Illustrating basic approaches of business intelligence to the more complex methods of data and text mining, the book guides readers through the process of extracting valuable knowledge from the varieties of data currently being generated in the brick and mortar and internet environments. It considers the broad spectrum of analytics approaches for decision making, including dashboards, OLAP cubes, data mining, and text mining.
- Includes a foreword by Thomas H. Davenport, Distinguished Professor, Babson College; Fellow, MIT Center for Digital Business; and Co-Founder, International Institute for Analytics
- Introduces text mining and the transforming of unstructured data into useful information
- Examines real time wireless medical data acquisition for today’s healthcare and data mining challenges
- Presents the contributions of big data experts from academia and industry, including SAS
- Highlights the most exciting emerging technologies for big data―Hadoop is just the beginning
Filled with examples that illustrate the value of analytics throughout, the book outlines a conceptual framework for data modeling that can help you immediately improve your own analytics and decision-making processes. It also provides in-depth coverage of analyzing unstructured data with text mining methods to supply you with the well-rounded understanding required to leve
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 Belt
Dr. 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 University
Just 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
