Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th edition
Published by Pearson (January 13, 2017) © 2017
- Ramesh Sharda Oklahoma State University
- Dursun Delen Oklahoma State University
- Efraim Turban Oklahoma State University , University of Hawaii
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For courses in Business Intelligence or Decision Support Systems.
A managerial approach to understanding business intelligence systems
Business Intelligence, Analytics, and Data provides students with a solid foundation in business intelligence (BI), reinforced with hands-on practice to help future managers use and understand analytics. Real-world cases throughout illustrate the capabilities, costs and justifications of BI as applied to a variety of businesses.
The 4th Edition has been reorganized around 3 types of analytics: descriptive, predictive, and prescriptive (a classification promoted by INFORMS), and includes new exercises, Internet assignments, and discussion questions.
Hallmark features of this title
Real-world focus
- The text takes a managerial approach to Business Intelligence technologies preparing students for managerial roles.
- Real-world cases illustrate the capabilities, costs and justifications of BI as applied to diverse businesses. Opening Vignettes present BI problems and solutions, while Application Cases reinforce key concepts.
Structured for success
- Visuals support learning with boxed features highlighting key technology throughout and color charts, graphs, and figures illustrating data and processes.
- Learning is reinforced by chapter-ending highlights, key terms, and exercises, while section review questions assess for understanding of section concepts.
- A companion webpage provides student application exercise files and other resources.
New and updated features of this title
- NEW: Reorganized around 3 types of analytics: descriptive, predictive, and prescriptive (INFORMS classification).
- NEW: 3 new chapters cover the nature of data, statistical modeling, and data visualization (Ch. 2, includes new cases); prescriptive analytics and optimization modeling in Excel using linear programming (Ch. 6); and new phenomena already impacting or likely to impact analytics.
- REVISED: All 5 preexisting chapters are fully revised with new vignettes and cases, coverage of analytics in sports, analytics in the health care and retail industries, the analytics ecosystem, Teradata Aster, and alternative data.
- NEW: Now printed in color with enhanced visuals and a revised title, the text also benefits from new author team members Ramesh Sharda and Dursun Delen, who've built on the content of previous editions.
- NEW: The text's companion website (dssbibook.com) is up-to-date with links to related news stories, software, tutorials, and videos. Included are links to free software support, data mining, related exercises, and more via Teradata University Network (TUN).
- NEW: Activities have been added (e.g., exercises, Internet assignments, and discussion questions). In addition, applications cases have been updated to include recent examples related to specific techniques and models.
Highlights of the DIGITAL UPDATE (available for Spring 2021 classes)
Instructors, contact your sales rep to ensure you have the most recent version of the course.
- All chapter references and URLs, specifically relating to application cases, have been updated.
- Coverage of Teradata Learning for Academics has been updated throughout the book.
- Updates reflect the impacts of Covid-19 on the analytics profession, as well as opportunities for employing analytics in this arena.
- An Overview of Business Intelligence, Analytics, and Data Science
- Descriptive Analytics I: Nature of Data, Statistical Modeling, and Visualization
- Descriptive Analytics II: Business Intelligence and Data Warehousing
- Predictive Analytics I: Data Mining Process, Methods, and Algorithms
- Predictive Analytics II: Text, Web, and Social Media Analytics
- Prescriptive Analytics: Optimization and Simulation
- Big Data Concepts and Tools
- Future Trends, Privacy and Managerial Considerations in Analytics
About our authors
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 systems, 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 several 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 analytics, 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 intelligence 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, business 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.
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