Business Intelligence, Analytics, Data Science, and AI, Global Edition, 5th edition

Published by Pearson (June 10, 2024) © 2024

  • Ramesh Sharda Oklahoma State University
  • Dursun Delen Oklahoma State University
  • Efraim Turban Oklahoma State University , University of Hawaii

eTextbook

from£28.99

  • Create notes, highlights and flashcards
  • Intuitive search, video, quizzes and interactive features
  • Translate text on-screen into over 100 languages
  • Audiobook for on-the-go learning
  • AI-powered support*
  • 3 months free access to language learning support with Mondly

*Available for some titles

£62.99

  • A print text (hardcover or paperback)
  • Free shipping

For 1 or 2-semester courses in business intelligence, data science, business analytics and MIS.

Analytics and AI for tomorrow's managers

Business Intelligence, Analytics, Data Science, and AI helps students understand the business-related impact of artificial intelligence, data science and analytics and prepares them for managerial roles. Vignettes and cases illustrate capabilities and costs of data science and analytics, as used by current businesses, while hands-on practice helps future managers use analytics effectively.

The 5th Edition integrates the fully updated content of Analytics, Data Science, and AI, 11/e and Business Intelligence, Analytics, and Data Science, 4/e into one textbook, strengthened by 4 all-new chapters that empower future managers to master today's analytics and AI tech, such as ChatGPT.

Hallmark features of this title

  • Prepares tomorrow's managers for roles in decision support systems, business intelligence (BI) and analytics, emphasizing methods, software and the role of Artificial Intelligence (AI).
  • Opening vignettes and application cases present BI problems and solutions, apply specific techniques or models, and illustrate how organizations use analytics and AI technology effectively.
  • Real-world cases and examples demonstrate capabilities, costs and justifications of BI.
  • Boxed features call out key technology; color charts, graphs and figures illustrate data and processes.
  • Chapter highlights, key terms, exercises, section review questions and Internet assignments provide hands-on practice.
  • Pearsonhighered.com/sharda offers application exercise files and other key resources.

New and updated features of this title

  • NEW: Integrates the fully updated content of Analytics, Data Science, and AI, 11/e and Business Intelligence, Analytics, and Data Science, 4/e into one textbook, strengthened by 4 all-new chapters that empower future managers to master today's analytics and AI technologies.
  • REVISED: Streamlined and organized around 3 types of business analytics, descriptive, predictive and prescriptive (INFORMS classification), the text offers 11 chapters in 5 sections that provide exposure, experience and opportunity for exploration.
  • NEW: An all-new chapter on tools for analytics provides an overview and guidance to use R/Python, KNIME, JMP and more.
  • NEW: 4 all-new and 7 fully updated chapters cover the latest in analytics and AI, such as ChatGPT, and pinpoint the relevance of each innovation (conversational AI, machine and deep learning, cloud-based analytics, IoT, Metaverse, etc.) to analytics.
  • NEW: Vignettes and cases illustrate modern companies using techniques covered across a range of business units. New examples include analytics in sports, the gaming industry, agriculture, and “data for good.”
  • NEW: Updated coverage of ethical, privacy and managerial considerations in analytics includes new issues related to responsible AI, protection of privacy, IP, technical and administrative concerns and consequences.
  1. An Overview of Business Intelligence, Analytics, Data Science, and AI
  2. Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications
  3. Descriptive Analytics I: Nature of Data, Big Data, and Statistical Modeling
  4. Descriptive Analytics II: Business Intelligence Data Warehousing, and Visualization
  5. Predictive Analytics I: Data Mining Process, Methods, and Algorithms
  6. Predictive Analytics II: Text, Web, and Social Media Analytics
  7. Deep Learning and Cognitive Computing
  8. Prescriptive Analytics: Optimization and Simulation
  9. Landscape of Business Analytics Tools
  10. AI-Based Trends in Analytics and Data Science
  11. Ethical, Privacy, and Managerial Considerations in Analytics

About our authors

Ramesh Sharda (MBA, PhD, 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 (OSU). 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 the Journal of MIS. He cofounded the AIS SIG on Decision Support Systems and Knowledge Management (SIGDSA). Dr. Sharda serves on several editorial boards, including those of Decision Support Systems and ACM Data Base. He has authored and edited several textbooks and research books and serves as the coeditor of several Springer book series (Integrated Series in Information Systems, Operations Research/Computer Science Interfaces, and Annals of Information Systems) with Springer. He served as the Executive Director of the Teradata University Network from 2013-2020. His current research interests are in decision support systems, business analytics, and technologies for managing information overload. Ramesh is a Fellow of INFORMS and AIS, and was inducted into the Oklahoma Higher Education Hall of Fame in 2015. He was awarded a Fulbright Distinguished Chair at Aalto University of Finland for spring 2023.

Dursun Delen (PhD, 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 5 years, during which he led a number of decision support and other information systems–related research projects funded by several federal agencies including the 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 200 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/coauthored twelve 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 regularly chairs, tracks, and minitracks at various information systems and analytics conferences. He is currently serving as the Editor-in-Chief for the Journal of Business Analytics, Journal of AI in Business (part of Frontiers in AI family of journals), and as Senior Editor, Associate Editor, or Editorial Board Member for more than another dozen of academic journals. His research and teaching interests are in data and text mining, business analytics, decision support systems, data science, knowledge management, business intelligence, and enterprise modeling.

Efraim Turban (MBA, PhD., 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 Systems. 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.

Need help? Get in touch

Pearson eText

Extend learning beyond the classroom. Pearson eText is an easy-to-use digital textbook. It lets students customise how they study and learn with enhanced search and the ability to create flashcards, highlight and add notes all in one place. The mobile app lets students learn wherever life takes them, offline or online.

Video
Play
Privacy and cookies
By watching, you agree Pearson can share your viewership data for marketing and analytics for one year, revocable by deleting your cookies.

Pearson eTextbook: What’s on the inside just might surprise you

They say you can’t judge a book by its cover. It’s the same with your students. Meet each one right where they are with an engaging, interactive, personalized learning experience that goes beyond the textbook to fit any schedule, any budget, and any lifestyle.