Business Intelligence, Analytics, and Data Science A Managerial Perspective

by Sharda, Ramesh; Delen, Dursun; Turban, Efraim

• ISBN13: 9780134633282
• ISBN10: 0134633288
• Additional ISBN(s): 9780133051056, 9780134635248, 9780134635316
• Edition: 4th
• Format: Paperback
• Copyright: 2017-01-13
• Publisher: Pearson
• More Book Details

Summary

For courses on Business Intelligence or Decision Support Systems.

A managerial approach to understanding business intelligence systems.

To help future managers use and understand analytics, Business Intelligence provides students with a solid foundation of BI that is reinforced with hands-on practice.

Author Biography

Ramesh Sharda (M.B.A., Ph.D., University of Wisconsin—Madison)  is the Vice Dean  for Research and Graduate  Programs,  Watson/ConocoPhillips Chair and a Regents Professor of Management  Science  and  Information  Systems  in  the  Spears  School  of Business  at Oklahoma  State University. He cofounded and  directed  OSU’s PhD in Business  for the Executives  Program.  About  200 papers  describing  his research  have  been  published in major journals, including Operations Research, Management Science, Information Systems Research, Decision Support Systems, and  Journal of MIS. He cofounded the  AIS SIG on Decision  Support  Systems and  Knowledge  Management  (SIGDSS). Dr. Sharda serves  on several editorial boards, including those of Decision Sciences Journal, Decision Support Systems, and ACM Data Base. He has authored and edited several textbooks  and research books  and serves as the co-editor  of several book  series (Integrated  Series in Information Systems, Operations Research/Computer Science Interfaces, and Annals of Information Systems)  with  Springer.  He  is  also  currently  serving  as  the  executive  director  of  the Teradata  University Network.  His current  research  interests  are in decision  support  sys- tems, business  analytics, and technologies for managing  information  overload.

Dursun  Delen (Ph.D.,  Oklahoma   State  University)  is  the  Spears  Endowed   Chair  in Business  Administration,  Patterson   Foundation  Endowed   Chair  in  Business  Analytics, Director of Research for the Center for Health Systems Innovation,  and Regents Professor of Management  Science  and  Information  Systems  in  the  Spears  School  of Business  at Oklahoma  State University (OSU). Prior to his academic  career, he worked  for a privately owned  research  and  consultancy  company, Knowledge  Based  Systems Inc., in College Station, Texas, as a research  scientist  for five years,  during  which  he  led  a number  of decision  support  and other  information  systems—related research  projects funded  by sev- eral federal  agencies  including  Department of Defense  (DoD), National Aeronautics  and Space  Administration  (NASA), National  Institute  for  Standards  and  Technology  (NIST), Ballistic Missile Defense  Organization (BMDO), and  Department of Energy  (DOE). Dr. Delen has published more than 100 peer reviewed  articles, some of which have appeared in major journals like Decision Sciences, Decision Support Systems, Communications of the ACM, Computers and  Operations Research, Computers in Industry,  Journal of Production Operations  Management, Artificial  Intelligence  in  Medicine,  International  Journal  of Medical Informatics, Expert Systems with Applications, and IEEE Wireless Communications. He recently authored/co-authored seven textbooks  in the broad  areas of business  analyt- ics, data  mining,  text mining,  business  intelligence  and  decision  support  systems.  He is often  invited  to national  and  international  conferences for keynote  addresses on  topics related  to data/text mining,  business  analytics, decision  support  systems,  business  intel- ligence and knowledge management. He served as the general cochair for the Fourth International Conference on Network Computing and Advanced Information Management (September  2—4, 2008, in Soul, South Korea) and regularly chairs tracks and mini-tracks at various  information  systems and analytics conferences. He is currently  serving as editor- in-chief, senior editor, associate editor or editorial board member for more than a dozen academic  journals. His research  and teaching  interests  are in data and text mining, busi- ness analytics, decision  support  systems, knowledge management, business  intelligence, and enterprise modeling.

Efraim Turban (M.B.A., Ph.D., University of California, Berkeley) is a visiting scholar at the Pacific Institute for Information System Management, University of Hawaii. Prior to this, he was on the staff of several universities, including City University of Hong Kong, Lehigh University, Florida International University, California State University, Long Beach; Eastern Illinois University, and the University of Southern California. Dr. Turban is the author of more than 100 refereed papers published in leading journals, such as "Management Science", "MIS Quarterly", and "Decision Support System". He is also the author of 20 books, including "Electronic Commerce: A Managerial Perspective" and "Information Technology for Management". He is also a consultant to major corporations worldwide. Dr. Turban's current areas of interest are Web-based decision support systems, social commerce, and collaborative decision making.

Table of Contents

Chapter 1     An Overview of Business Intelligence, Analytics, and Data Science                                    3

Chapter 2     Descriptive Analytics I: Nature of Data, Statistical Modeling, and Visualization                  53

Chapter 3     Descriptive Analytics II: Business Intelligence and Data Warehousing                              127

Chapter 4     Predictive Analytics I: Data Mining Process, Methods, and Algorithms                              189

Chapter 5     Predictive Analytics II: Text, Web, and Social Media Analytics                                         247

Chapter 6     Prescriptive Analytics: Optimization and Simulation                                                        319

Chapter 7     Big Data Concepts and Tools                                                                                        369

Chapter 8     Future Trends, Privacy and Managerial Considerations in Analytics                                   417