Data Analytics for Business: Foundations and Industry Applications

289 Pages·2022·5.22 MB·English

by  Fenio Annansingh, Joseph Bon Sesay

Data Analytics for Business
Data analytics underpin our modern data-driven economy. This textbook
explains the relevance of data analytics at the firm and industry levels, tracing
the evolution and key components of the field, and showing how data analyt-
ics insights can be leveraged for business results.
The first section of the text covers key topics such as data analytics tools, data
mining, business intelligence, customer relationship management, and cyber-
security. The chapters then take an industry focus, exploring how data analyt-
ics can be used in particular settings to strengthen business decision-making.
A range of sectors are examined, including financial services, accounting,
marketing, sport, health care, retail, transport, and education. With industry
case studies, clear definitions of terminology, and no background knowledge
required, this text supports students in gaining a solid understanding of data
analytics and its practical applications. PowerPoint slides, a test bank of ques-
tions, and an instructor manual are also provided as online supplements.
This will be a valuable text for undergraduate level courses in data analyt-
ics, data mining, business intelligence, and related areas.
Fenio Annansingh is currently an Associate Professor at York College, City
University of New York, where she teaches Information Systems, Project and
Operations Management classes. Her main area of research is Information
Systems in two key areas, namely Information Management and Knowledge
Management. Her research interest includes knowledge leakage, Information
System Risk Management, Smart and Mobile technologies, and Cybersecu-
rity education organisations. Dr. Annansingh has several publications and
professional papers with several affiliates.
Joseph Bon Sesay is a Certified Public Accountant (CPA) and a Chartered
Global Management Accountant (CGMA). He teaches at York College, City
University of New York (CUNY), and has over 20 years of experience in senior
and management positions with Multinational Corporations such as Viacom/
CBS, Interpublic Group (IPG)/Mediabrands, and Publicis/Mediavest World-
wide. Dr. Sesay holds a doctorate and an MBA in Finance from Pace Uni-
versity, New York City, New York, and Master of Liberal Arts in Extension
Studies in Government from Harvard University, Cambridge, Massachusetts.

Data Analytics for Business
Foundations and Industry Applications
Fenio Annansingh and
Joseph Bon Sesay
Cover image: © shulz / Getty Images
First published 2022
by Routledge
4 Park Square, Milton Park, Abingdon, Oxon OX14 4RN
and by Routledge
605 Third Avenue, New York, NY 10158
Routledge is an imprint of the Taylor & Francis Group, an informa business
© 2022 Fenio Annansingh and Joseph Bon Sesay
All rights reserved. No part of this book may be reprinted or
reproduced or utilised in any form or by any electronic, mechanical,
or other means, now known or hereafter invented, including
photocopying and recording, or in any information storage or
retrieval system, without permission in writing from the publishers.
Trademark notice: Product or corporate names may be trademarks
or registered trademarks, and are used only for identification and
explanation without intent to infringe.
British Library Cataloguing-in-Publication Data
A catalogue record for this book is available from the British Library
Library of Congress Cataloging-in-Publication Data
A catalog record has been requested for this book
ISBN: 978-0-367-65421-4 (hbk)
ISBN: 978-0-367-65419-1 (pbk)
ISBN: 978-1-003-12935-6 (ebk)
DOI: 10.4324/9781003129356
Typeset in Bembo
by codeMantra
Access the Support Material: www.routledge.com/9780367654191
Contents
List of figures vii
List of tables ix
Acknowledgements xi
1 History and Evolution of Data Analytics 1
2 Data Mining and Analytics 12
3 Data Analytics Tools 27
4 Business Analytics and Intelligence 48
5 Customer Relationship Analytics, Cloud Computing,
Blockchain, and Cognitive Computing 71
6 Cybersecurity and Data Analytics 91
7 Data Analytics and the Retail Industry 114
8 Data Analytics in the Financial Services Industry 131
9 Data Analytics in the Sports Industry 148
10 Data Analytics in the Accounting Industry 164
11 Data Analytics in the Medical Industry 182
12 Data Analytics in the Manufacturing Industry 199
13 Data Analytics in the Marketing Industry 215
vi Contents
14 Data Analytics in the Transportation Industry 233
15 Data Analytics in Education 250
Index 267
Figures
1.1 Relationship Between Data, Information, Knowledge, and
Wisdom. 4
1.2 Components of Data Science. 7
1.3 Fields of Data Science. 8
2.1 Summary of Data Mining Process. 15
2.2 Data Mining Techniques. 16
2.3 Data Mining: a Subset of Data Science. 22
3.1 Characteristics of Big Data. 29
3.2 Business Benefits of Big Data. 31
3.3 Drivers of Big Data. 32
3.4 Forces Driving Embedded Analytics. 45
4.1 Component of Business Intelligence. 55
4.2 Data Warehouse Architecture. 56
5.1 Types of Computing. 77
6.1 Security Analytics Process. 93
6.2 Security Analytics. 101
7.1 Big Data Usage in the Retail Industry. 116
7.2 Customer Analytics in the Retail Industry. 118
12.1 Manufacturing Analytics. 202
12.2 Maintenance Strategies. 207
12.3 Predictive Maintenance. 209
14.1 Components of Transportation. 235

Tables
1.1 Provides Examples of Data 3
1.2 Provides an Outline of the Intricate Relationship between
Data, Information and Knowledge 5
3.1 Strategic Benefits of Big Data 30
3.2 Customer Relationships and Sales Benefits of Big Data 31