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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.
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.
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