Big Data, Mining, and Analytics
Components of Strategic Decision Making
1st Edition
Published on 12. March 2014
326 pages
978-1-4665-6871-6 (ISBN)
Description
This book ties together big data, data mining, and analytics to explain how readers can leverage them to transform their business strategy. Illustrating basic approaches of business intelligence to 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.
Reviews / Votes
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 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 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
More details
Edition
1. Auflage
Language
English
Place of publication
Philadelphia, PA
United States
Publishing group
Taylor & Francis Inc
Target group
Professional and scholarly
Illustrations
89 s/w Abbildungen, 9 s/w Tabellen
89 b/w images, 9 tables and 7
File size
11,16 MB
ISBN-13
978-1-4665-6871-6 (9781466568716)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
10/2019
1st Edition
CRC Press
€76.81
Shipment within 15-20 days
Book
03/2014
1st Edition
Auerbach
€98.50
Shipment within 15-20 days
Person
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.
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.
Content
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.
