TY - BOOK
T1 - Big-data analytics and cloud computing: Theory, algorithms and applications
AU - Trovati, Marcello
AU - Hill, Richard
AU - Anjum, Ashiq
AU - Zhu, Shao Ying
AU - Liu, Lu
PY - 2016/1/1
Y1 - 2016/1/1
N2 - 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. © Springer International Publishing Switzerland 2016.
AB - 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. © Springer International Publishing Switzerland 2016.
U2 - 10.1007/978-3-319-25313-8
DO - 10.1007/978-3-319-25313-8
M3 - Book
SN - 9783319253138
BT - Big-data analytics and cloud computing: Theory, algorithms and applications
PB - Springer International Publishing AG
ER -