Big Data, Mining, and Analytics : Components of Strategic Decision Making

Title:

Personal Author:

Kudyba, Stephan, 1963-, author

Physical Description:

xv, 305 pages : illustrations (some color), color maps ; 24 cm

ISBN:

9780367378813

Abstract:

This book describes, the potential of big data is enabled by ubiquitous computing and data gathering devices; sensors and microprocessors will soon be everywhere. Virtually every mechanical or electronic device can leave a trail that describes its performance, location, or state. These devices, and the people who use them, communicate through the Internet which leads to another vast data source. When all these bits are combined with those from other media wireless and wired telephony, cable, satellite, and so forth the future of data appears even bigger. The availability of all this data means that virtually every business or organizational activity can be viewed as a big data problem or initiative. Manufacturing, in which most machines already have one or more microprocessors, is increasingly a big data environment. Consumer marketing, with myriad customer touchpoints and clickstreams, is already a big data problem. Google has even described its self-driving car as a big data project. Big data is undeniably a big deal, but it needs to be put in context.

Subject Term:

Strategic planning -- Data processing

Data mining

Big data

Business planning -- Data processing

Webometrics

Data loggers

Available:*

Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ KL	33000000006750	HD30.28 B54 2019	Open Access Book	Book	Searching... Unknown

On Order

Summary

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

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.

Author Notes

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.

Stephan Kudyba and Matthew KwatinetzStephan KudybaWullianallur Raghupathi and Viju RaghupathiWayne ThompsonStephan KudybaRobert YoungStephan KudybaBillie Anderson and J. Michael HardinSteven BarberMeta S. BrownIoannis KorkontzelosDavid Lubliner and Stephan Kudyba

Foreword	p. ix
About the Author	p. xiii
Contributors	p. xv
Chapter 1 Introduction to the Big Data Era	p. 1
Chapter 2 Information Creation through Analytics	p. 17
Chapter 3 Big Data Analytics-Architectures, Implementation Methodology, and Tools	p. 49
Chapter 4 Data Mining Methods and the Rise of Big Data	p. 71
Chapter 5 Data Management and the Model Creation Process of Structured Data for Mining and Analytics	p. 103
Chapter 6 The Internet: A Source of New Data for Mining in Marketing	p. 129
Chapter 7 Mining and Analytics in E-Commerce	p. 147
Chapter 8 Streaming Data in the Age of Big Data	p. 165
Chapter 9 Using CEP for Real-Time Data Mining	p. 179
Chapter 10 Transforming Unstructured Data into Useful Information	p. 211
Chapter 11 Mining Big Textual Data	p. 231
Chapter 12 The New Medical Frontier: Real-Time Wireless Medical Data Acquisition for 21st-century Healthcare and Data Mining Challenges	p. 257
Index	p. 307

Available:*

On Order

Summary

Summary

Author Notes

Table of Contents