Editors:
- Discusses and explores theoretical concepts, principles, tools, techniques and deployment models in the context of Big Data
- Focuses on the latest developments in Data Science (aka Analytics) and, especially, their applications to real-world challenges
- Includes numerous cases studies for in-class analysis and assignments
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Table of contents (10 chapters)
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Front Matter
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Applications
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Front Matter
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Back Matter
About this book
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.
Editors and Affiliations
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University of Derby, Derby, United Kingdom
Marcello Trovati, Richard Hill, Ashiq Anjum, Shao Ying Zhu, Lu Liu
About the editors
The editors are all members of the Computing and Mathematics Department at the University of Derby, UK, where Dr. 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, and Dr. Lu Liu as a Professor of Distributed Computing. The other publications of the editors include the Springer titles Guide to Security Assurance for Cloud Computing, Guide to Cloud Computing and Cloud Computing for Enterprise Architectures.
Bibliographic Information
Book Title: Big-Data Analytics and Cloud Computing
Book Subtitle: Theory, Algorithms and Applications
Editors: Marcello Trovati, Richard Hill, Ashiq Anjum, Shao Ying Zhu, Lu Liu
DOI: https://doi.org/10.1007/978-3-319-25313-8
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Hardcover ISBN: 978-3-319-25311-4Published: 19 January 2016
Softcover ISBN: 978-3-319-79767-0Published: 30 March 2018
eBook ISBN: 978-3-319-25313-8Published: 12 January 2016
Edition Number: 1
Number of Pages: XVI, 169
Number of Illustrations: 67 illustrations in colour
Topics: Probability and Statistics in Computer Science, Computer Communication Networks, Simulation and Modeling, Math Applications in Computer Science