Hands-on Data Analytics for Business

1. Auflage 2026
ISBN: 978-1-032-62736-6
Verlag: Taylor & Francis Ltd

Buch, Englisch, 192 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g

"Advancements in data analytics and the widespread use of large-scale data are driving a golden age of evidence-based management. This timely publication addresses limitations in traditional business school curricula.”–Professor Xu Huang, Associate Dean (Research and Impact) and Chair Professor in Management, School of Business, Hong Kong Baptist University

The knowledge and skills of data analytics enable business professionals to make evidence-based decisions rather than just by intuition. To appreciate the knowledge and skills, one needs to understand the theory, hands-on statistical operations using computer software, business application case studies and the analytics project maturity roadmap.

Hands-on Data Analytics for Business is a concise all-in-one analytics textbook for business professionals and university students who want to:

- Understand the essential theories and concepts of data analytics

- Grasp hands-on practical statistical and analytics skills step-by-step using SPSS and Excel

- Appreciate real-world well-known case studies in human resources, marketing and supply chain on how data analytics is applied in business.

This book is for business professionals or university students seeking to master data analytics knowledge and technical skills to a level allowing them to practice data analytics hands-on and manage data analytics projects at scale. For business professionals, the book is written in a way to help learn statistical skills in a concise way with practical real-world examples to inspire business applications. For students, this book is organized in a sequence readily deliverable for a university course with classes combining theory or concepts, hands-on practice and case studies. For all readers, the book is an essential guide on using data analytics to tackle modern complex activities for companies to gain a competitive edge.

Zielgruppe

Undergraduate Core

Autoren/Hrsg.

Tang, Monica W. M.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
• Wirtschaftswissenschaften Betriebswirtschaft Management

Inhaltsverzeichnis

1. Introduction to Data Analytics 2. The Data Analytics Process 3. Data Analytics in Human Resources 4. Data Analytics in Marketing 5. Data Analytics in Supply Chain 6. Building Analytics Capabilities, Running Projects and Future Trends

Über Autor(innen)

Dr. Monica W.M. Tang is Adjunct Associate Professor in Hong Kong Baptist University School of Business. She also teaches in The University of Hong Kong and other universities. She has been teaching different courses in the topic of Data Analytics for Business after she earned her Doctor of Business Administration in City University of Hong Kong in 2019. She received the “Outstanding Teacher Award” from The University of Hong Kong School of Professional and Continuing Education in 2024.

Dr. Tang is also a seasoned information technology (IT) management professional. She has more than 25 years’ working experience with a demonstrated history of successful IT projects in public sectors, universities and consulting companies. She is now Senior IT Manager in The University of Hong Kong. Her expertise areas include data analytics, digital transformation and project management in different business areas including human resources, finance and manufacturing.

Dr. Tang has a vision of bringing measurable benefits using data analytics from IT to organizations and employees. She wants to make a positive impact to the professional society by sharing the knowledge and skills in data analytics through different publications. She is a frequent speaker in seminars on analytics, artificial intelligence, management and leadership. She is also the awardee of “Contribution to the Society Award” by City University of Hong Kong in 2017.