Hands-on Data Analytics for Business

個数：

予約

Hands-on Data Analytics for Business

Tang, Monica W. M.

ウェブストア価格 ¥35,424（本体¥32,204）
Auerbach（2026/01発売）
外貨定価 US$ 170.00
ポイント 322pt

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製本 Hardcover:ハードカバー版／ページ数 192 p.
言語 ENG
商品コード 9781032627366

Full Description

"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.

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