Business Analytics

From Data to Decision
1. Auflage 2026
ISBN: 978-1-041-29509-9
Verlag: Taylor & Francis Ltd

Buch, Englisch, 526 Seiten, Format (B × H): 174 mm x 246 mm

Presenting and Modeling Business Data is a comprehensive, practical guide on how to develop raw data into valuable structures for business decision-making. The authors are experienced, highly respected educators and practitioners of accounting, law, and analytics. They are acknowledged experts on the role of generative AI in education and assessment. This book emphasizes critical thinking, data quality, the art of storytelling, and compelling presentation skills as essential workplace attributes. Beyond theoretical discourse, dedicated chapters train the reader in using vital software including Solver, Power BI, and regression techniques.

Key features include:

• A step-by-step framework for evaluating, visualizing, and analyzing business data.

• Extensive illustration of common data biases, and errors, and techniques for avoiding them.

• Practical, hands-on guidance on designing effective charts, dashboards, and presentations which really resonate with audiences.

• Instruction on using Excel, Solver, and Power BI for analytics and forecasting.

• A comprehensive start-to finish demonstration of modeling for a complex business.

• Real-world examples drawn from multiple disciplines.

• Multiple choice questions to reinforce key concepts.

• Downloadable datasets, templates, and solutions for hands-on practice.

Although primarily written for undergraduate and graduate business students, this book is also of value to professionals seeking to strengthen their data and communication skills. It forms the bridge from technical competence to clear communication, enabling users to present insights from data in a clear and convincing manner.

Zielgruppe

Postgraduate, Professional Practice & Development, and Undergraduate Advanced

Autoren/Hrsg.

Davis, Paul

Amlani, Alym

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensfinanzen
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsvisualisierung
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmenskommunikation
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensorganisation, Corporate Responsibility Unternehmensethik
• Wirtschaftswissenschaften Betriebswirtschaft Management Unternehmensorganisation & Entwicklungsstrategien

Inhaltsverzeichnis

PART I: ANALYTICAL FOUNDATIONS  Chapter 1: What is analytics?  Chapter 2: Data, evidence, and claims  Chapter 3: Data provenance  Chapter 4: Data collection: Design, sampling, and structure  Chapter 5: Perception and cognitive bias  Chapter 6: Reasoning, inference, and analytical fallacies  Chapter 7: Ethical responsibility, defensibility, and disclosure  PART II: THE NATURE AND STRUCTURE OF DATA  Chapter 8: Data types, tables, datasets, and databases  Chapter 9: Structured data in practice  Chapter 10: Data beyond tables  Chapter 11: Preparing data for analysis  PART III: ANALYTICS AND INFERENCE  Chapter 12: Tools for business analytics  Chapter 13: Framing questions and problems  Chapter 14: Descriptive analytics: What has happened?  Chapter 15: Time series analysis and basic forecasting  Chapter 16: Patterns and relationships  Chapter 17: Sampling, uncertainty, and estimation  Chapter 18: Hypothesis testing, statistical significance, and causal claims  Chapter 19: Linear regression and the evaluation of relationships  Chapter 20: Model validation and the limits of inference  PART IV: VISUALIZATION FOR ANALYTICS  Chapter 21: Why visualization? Charts are arguments  Chapter 22: Principles of data visualization  Chapter 23: Chart types and visual distortions  PART V: DECISIONS, COMMUNICATION, AND THE FUTURE  Chapter 24: Decision support, sensitivity analysis, and optimization under uncertainty  Chapter 25: Financial and investment decisions  Chapter 26: Financial modeling  Chapter 27: Narrative, persuasion, and ethical influence  Chapter 28: Oral presentation  Chapter 29: Dashboards and organizational reporting  Chapter 30: The future of business analytics

Über Autor(innen)

Alym Amlani CPA, CA, is an accomplished educator and author. He specializes in business analytics, accounting, information systems, and emerging technologies. He currently teaches at the University of British Columbia (Sauder) and Kwantlen Polytechnic University (Melville) Schools of Business. His research focuses on the practical application of data, financial analysis, technology, and decision-making at the intersection with Artificial Intelligence.

Paul Davis MBA, LLD, is an educator, author, and researcher with four decades of experience in law, finance, business, and accounting. He began his professional career as an Assistant Professor of Law at the University of Ottawa, then founded several successful businesses before returning to academia in 2020. His research and writing range from criminal sentencing to ethics, judgment, and emerging technologies in education, with particular emphasis on communication and the responsible use of new technologies.