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

  • Ramesh Sharda
  • , Dursun Delen
  • , Efraim Turban

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Business Intelligence, Analytics, Data Science, and AI is your guide to the business-related impact of artificial intelligence, data science and analytics, designed to prepare you for a managerial role. The text's vignettes and cases feature modern companies and non-profit organizations and illustrate capabilities, costs and justifications of BI across various business units. With coverage of many data science/AI applications, you'll explore tools, then learn from various organizations' experiences employing such applications. Ample hands-on practice is provided, can be completed with a range of software, and will help you use analytics as a future manager.

The 5th Edition integrates the fully updated content of Analytics, Data Science, and Artificial Intelligence, 11/e and Business Intelligence, Analytics, and Data Science, 4/e into one textbook, strengthened by 4 new chapters that will equip you for today's analytics and AI tech, such as ChatGPT. Examples explore analytics in sports, gaming, agriculture and “data for good.”

Published by Pearson (August 30th 2023) - Copyright © 2024

ISBN-13: 9780138043308

Subject: Management Information Systems

Category: Business Intelligence / Analytics

  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