Big-Data Analytics and Cloud Computing
Theory, Algorithms and Applications
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.
| ISBN: | 9783319253114 |
|---|---|
| Sprache: | Englisch |
| Seitenzahl: | 169 |
| Produktart: | Gebunden |
| Herausgeber: | Anjum, Ashiq Hill, Richard Liu, Lu Trovati, Marcello Zhu, Shao Ying |
| Verlag: | Springer International Publishing |
| Veröffentlicht: | 19.01.2016 |
| Untertitel: | Theory, Algorithms and Applications |
| Schlagworte: | Analytics Big Data Cloud Computing Distributed Systems Simulation and Modeling |
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