Obtaining Value from Big Data for Service Systems, Volume I: Big Data Management

137 Pages·2019·2.454 MB·English

by  Steven H. Kaiser, Frank Armour, J. Alberto Espinosa, William H. Money

Obtaining Value from Big Data K Service Systems and Innovations
THE BUSINESS A
EXPERT PRESS for Service Systems, Volume I ISL in Business and Society Collection
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DIGITAL LIBRARIES R Jim Spohrer and Haluk Demirkan, Editors
Big Data Management •
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EBOOKS FOR Second Edition M
BUSINESS STUDENTS O
U Obtaining Value
Curriculum-oriented, born- Stephen H. Kaisler • Frank Armour • R
digital books for advanced J. Alberto Espinosa • William H. Money • E
business students, written S from Big Data
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by academic thought Volume I of this two-volume series focuses on the role of big data IN
in service delivery systems. It discusses the defi nition and orien- O
leaders who translate real-
tation to big data, applications of it in service delivery systems, S for Service
world business experience A
how to obtain results that can affect/enhance service delivery, •
into course readings and and how to build an effective big data organization. M
reference materials for This volume will assist readers in fi tting big data analysis O Systems, Volume I
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students expecting to tackle into their service-based organizations. It will also help readers E
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management and leadership understand how to improve the use of big data to enhance their
challenges during their service-oriented organizations. Big Data Management
professional careers.
Stephen H. Kaisler is consultant at SHK & Associates and
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adjunct professor of engineering at George Washington Univer-
POLICIES BUILT B
BY LIBRARIANS sity. He has focused his efforts on Big Data and analytics, and TA Second Edition
enterprise architecture. He has published over 45 papers and I
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• Unlimited simultaneous 11 books on varied subjects such as Big Data and Historical Com- I
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usage puting Machines. G
• Unrestricted downloading V
Frank Armour is assistant professor in the Kogod School of Busi- A
and printing L
ness at the American University and the faculty program direc- U
• Perpetual access for a tor for the MS degree program in analytics. He has over 25 years E
one-time fee of extensive experience in both the practical and academic FR
• No platform or aspects of applying advanced information technology. O Stephen H. Kaisler
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maintenance fees J. Alberto Espinosa is professor and former chair of information B
• Free MARC records technology in the Kogod School of Business at the American Uni- IG Frank Armour
• No license to execute D
versity. His research focuses on coordination in global technic- A
The Digital Libraries are a al projects across global boundaries, particularly distance and TA J. Alberto Espinosa
comprehensive, cost-eff ective time. He published in various journals including IEEE Transac- F
tions on Software Engineering and IEEE Transactions on Engineering O
way to deliver practical R William H. Money
Management. S
treatments of important E
William H. Money is associate professor at the Baker School R
business issues to every V
of Business, The Citadel. His recent research interests focus on I
student and faculty member. C
collaborative solutions to complex business problems; business E
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process engineering, analytics; and information system develop- Y
ment, collaboration, and methodologies. He has signifi cant S
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consulting experience in private organizations and the federal E
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For further information, a government.
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free trial, or to order, contact:  , V
Service Systems and Innovations O
[email protected] in Business and Society Collection LU
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www.businessexpertpress.com/librarians
Jim Spohrer and Haluk Demirkan, Editors E
I
Obtaining Value from Big
Data for Service Systems,
Volume I

Obtaining Value from Big
Data for Service Systems,
Volume I
Big Data Management
Second Edition
Stephen H. Kaisler
Frank Armour
J. Alberto Espinosa
William H. Money
Obtaining Value from Big Data for Service Systems, Second Edition,
Volume-I: Big Data Management
Copyright © Business Expert Press, LLC, 2019.
All rights reserved. No part of this publication may be reproduced, stored
in a retrieval system, or transmitted in any form or by any means—
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brief quotations, not to exceed 250 words, without the prior permission
of the publisher.
First published in 2019 by
Business Expert Press, LLC
222 East 46th Street, New York, NY 10017
www.businessexpertpress.com
ISBN-13: 978-1-94944-355-4 (paperback)
ISBN-13: 978-1-94944-356-1 (e-book)
Business Expert Press Service Systems and Innovations in Business and
Society Collection
Collection ISSN: 2326-2664 (print)
Collection ISSN: 2326-2699 (electronic)
Cover and interior design by S4Carlisle Publishing Services Private Ltd.,
Chennai, India
First edition: 2016
Second edition: 2019
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Printed in the United States of America.
Dedication
I would like to dedicate this book to my wife, Chryl, who has encouraged me
and supported me in its preparation.
—Stephen H. Kaisler
I would like to thank my wife, Delphine Clegg, for her support and
encouragement in preparing this book.
—J. Alberto Espinosa
To my wife, Rose, my parents, my children, and my grandchild: you make
everything beautiful.
—Frank Armour
To my wonderful wife, Libby, whose continuous support and strength allow
me to devote more energy to research and writing, and to my daughter,
Katy, whose enduring dedication and commitment have taught me how to
successfully close a project.
—William H. Money

Abstract
Big data is an emerging phenomenon that has enormous implications and
impacts upon business strategy, profitability, and process improvements.
All service systems generate big data these days, especially human-centered
service systems such as government (including cities), health care, educa-
tion, retail, finance, and so on. It has been characterized as the collection,
analysis, and use of data characterized by the five Vs: volume, velocity,
variety, veracity, and value (of data). As the plethora of data sources grows
from sensors, social media, and electronic transactions, new methods for
collecting or acquiring, integrating, processing, analyzing, understanding,
and visualizing data to provide actionable information and support inte-
grated and timely senior and executive decision making are required. The
discipline of applying analytic processes to find and combine new sources
of data and extract hidden crucial decision-making information from the
oceans of data is rapidly developing, but requires expertise to apply in
ways that will yield useful, actionable results for service organizations.
Many service-oriented organizations that are just beginning to invest in
big data collection, storage, and analysis need to address the numerous
issues and challenges that abound—technological, managerial, and legal.
Other organizations that have begun to use new data tools and techniques
must keep up with the rapidly changing and snowballing work in the
field. This booklet will help middle, senior, and executive managers to un-
derstand what big data is: how to recognize, collect, process, and analyze
it; how to store and manage it; how to obtain useful information from it;
and how to assess its contribution to operational, tactical, and strategic
decision making in service-oriented organizations.
Keywords
analytic science; big data; business analytics; business intelligence; data
science; descriptive analytics; enterprise architecture; NoSQL; predictive
analytics; service delivery; service-oriented architecture

Contents
Purpose .................................................................................................xi
Acknowledgments .................................................................................xiii
List of Acronyms ...................................................................................xv
Chapter 1 Introduction .....................................................................1
Chapter 2 Applications of Big Data to Service Delivery .....................9
Chapter 3 Analyzing Big Data for Successful Results .......................23
Chapter 4 Building an Effective Big Data Organization ...................61
Appendix .............................................................................................95
References .............................................................................................97
Further Reading .................................................................................105
Glossary .............................................................................................107
About the Contributors .......................................................................109
Index .................................................................................................113