Big Data Management
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Beschreibung
This book focuses on the analytic principles of business practice and big data. Specifically, it provides an interface between the main disciplines of engineering/technology and the organizational and administrative aspects of management, serving as a complement to books in other disciplines such as economics, finance, marketing and risk analysis. The contributors present their areas of expertise, together with essential case studies that illustrate the successful application of engineering management theories in real-life examples.
This book focuses on the analytic principles of business practice and big data. Specifically, it provides an interface between the main disciplines of engineering/technology and the organizational and administrative aspects of management, serving as a complement to books in other disciplines such as economics, finance, marketing and risk analysis. The contributors present their areas of expertise, together with essential case studies that illustrate the successful application of engineering management theories in real-life examples.
Provides an interdisciplinary approach to big data, merging the perspectives of contributors from various fields of research Aimed at engineers, economists, and researchers who employ engineering management in the course of their work Offers insightful real-life case studies to illustrate the applications of big data in management Includes supplementary material: sn.pub/extras
Autor*in
Fausto Pedro García Márquez
Themen in »Big Data Management«
Big Data Business Analytics Operations Research Business Engineering IT Management Engineering Economics
Stimmen zu »Big Data Management«
“This book is definitely timely with its ambitious goals to fulfill a big gap in the literature. … this book provides a valuable collection of perspectives that demonstrate the complexity and diversity of big data, and open avenues for future research. … This book will be particularly welcome by researchers who are interested in an interdisciplinary approach to big data and have a basic understanding of computer science.” (Mingming Cheng, Information Technology & Tourism, Vol. 17, 2017)
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