Big-data Analytics and Cloud Computing ― Theory, Algorithms and Applications
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商品簡介
This book reviews the theoretical concepts, leading-edge techniques and practical tools involved in the latest multi-disciplinary approaches addressing the challenges of big data. Illuminating perspectives from both academia and industry are presented by an international selection of experts in big data science. Topics and features: describes the innovative advances in theoretical aspects of big data, predictive analytics and cloud-based architectures; examines the applications and implementations that utilize big data in cloud architectures; surveys the state of the art in architectural approaches to the provision of cloud-based big data analytics functions; identifies potential research directions and technologies to facilitate the realization of emerging business models through big data approaches; provides relevant theoretical frameworks, empirical research findings, and numerous case studies; discusses real-world applications of algorithms and techniques to address the challenges of big datasets.
作者簡介
The editors are all members of the Computing and Mathematics Department at the University of Derby, UK, whereDr. Marcello Trovati serves as a Senior Lecturer in Mathematics, Dr. Richard Hill as a Professor and Head of the Computing and Mathematics Department,Dr. Ashiq Anjum as a Professor of Distributed Computing, Dr. Shao Ying Zhu as a Senior Lecturer in Computing, andDr. Lu Liu as a Professor of Distributed Computing. The other publications of the editors include the Springer titlesGuide to Security Assurance for Cloud Computing, Guide to Cloud Computing andCloud Computing for Enterprise Architectures.
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