Business Analytics and Artificial Intelligence

Concepts, Skills and Real World Application
1. Auflage 2026
ISBN: 978-1-041-12402-3
Verlag: Taylor & Francis Ltd

Buch, Englisch, 366 Seiten, Format (B × H): 174 mm x 246 mm

Business Analytics and Artificial Intelligence provides an in-depth exploration of the intersection of business analytics, machine learning, and artificial intelligence (AI). Tailored for undergraduate, graduate, and professional learners, it equips readers with the knowledge and skills to leverage data-driven insights and AI technologies for strategic decision-making, operational optimization, and innovation in a dynamic global business environment. This book bridges the gap between theory and practice by:

- Introducing the foundational principles of business analytics and AI

- Demonstrating the integration of advanced AI techniques into business analytics processes  - Providing a unified guide to business analytics and machine learning with a focus on real-world applications

- Presenting a clear, practical, and accessible framework to harness AI and machine learning for solving complex business problems, optimizing operations, and driving innovation

- Exploring the ethical, legal, and social implications of AI in business contexts

- Presenting case studies and real-world applications from diverse industries to showcase best practices.

The textbook combines foundational concepts, advanced techniques, and hands-on applications, catering to readers with varying levels of technical expertise. It includes global perspectives of BA and AI, case studies, practical examples, and coding snippets (in Python or R) to help readers implement AI-driven solutions in their organizations. Topics span predictive analytics, machine learning, data visualization, natural language processing, and decision support systems, emphasizing how these tools empower businesses to stay competitive and ensure operational sustainability.

Zielgruppe

Postgraduate and Undergraduate Advanced

Autoren/Hrsg.

Rezaee, Zabihollah

Zhang, Joseph H.

Boumediene, Salem Lotfi

Rezaee, Nick J.

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Management Forschung & Entwicklung (F&E), Innovation
• Wirtschaftswissenschaften Betriebswirtschaft Organisationstheorie, Organisationssoziologie, Organisationspsychologie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Wirtschaftswissenschaften Betriebswirtschaft Management Unternehmensorganisation & Entwicklungsstrategien

Inhaltsverzeichnis

Chapter 1: Introduction to Business Analytics and Artificial Intelligence Chapter 2: Data Science Fundamentals Chapter 3: Business Statistics and Analytics Chapter 4: Machine Learning Essentials Chapter 5: Business Analytics Tools and Techniques Chapter 6: AI-Driven Business Strategies Chapter 7: Natural Language Processing (NLP) Chapter 8: Prescriptive Analytics and Optimization Chapter 9: Predictive Analytics and Forecasting Chapter 10: Advanced Machine Learning Techniques Chapter 11: Deep Learning and Neural Networks Chapter 12: AI and Business Analytics in Business and Industry Chapter 13: Responsible and Ethical AI and BA Frameworks Chapter 14: AI-Driven Analytics and Organizational Transformation Chapter 15: Emerging Issues of BA and AI in Business

Über Autor(innen)

Zabihollah Rezaee is the Thompson-Hill Chair of Excellence and Professor of Accountancy at the University of Memphis and has served a two-year term on the Standing Advisory Group of the Public Company Accounting Oversight Board (PCAOB).

Joseph H. Zhang is the Department Chair and the Robert W. and Patricia A. Maurer Family Distinguished Endowed Professor in the Department of Accounting and Management Information Systems at Bowling Green State University (BGSU) in Ohio, USA.

Salem Lotfi Boumediene is an Associate Professor at the University of Illinois Springfield (UIS) in the College of Business and Management.

Nick J. Rezaee is a graduate student in the Computational Biology and Quantitative Genetics program and programmer at the Harvard T.H Chen School of Public Health