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Book
High-Performance Big-Data Analytics : Computing Systems and Approaches
Authors: --- --- ---
ISBN: 9783319207438 9783319207445 331920744X 3319207431 Year: 2015 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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Abstract

This important and timely text/reference presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics.  Comprehensively covering a diverse range of computer systems and proven techniques for high-performance big-data analytics, the book also presents case studies, practical guidelines, and best practices for enabling decision-making toward implementing the appropriate computer systems and approaches. Topics and features: Includes case studies and learning activities throughout the book, and self-study exercises at the end of every chapter Presents detailed case studies on social media analytics for intelligent businesses, and on big data analytics in the healthcare sector Describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data Examines real-time analytics solutions, such as machine data analytics and operational analytics Introduces in-database processing and in-memory analytics techniques for data mining Discusses the use of mainframes for handling real-time big data, and the latest types of data management systems for big and fast data analytics Provides information on the use of cluster, grid and cloud computing systems for big data analytics and data-intensive processing Reviews the peer-to-peer techniques and tools, and the common information visualization techniques, used in big data analytics Software engineers, cloud professionals and big data scientists will find this book to be an informative and inspiring read, highlighting the indispensable role data analytics will play in shaping a smart future.

Keywords

Big data. --- High performance computing. --- Computer networks. --- Electronic data processing. --- Données volumineuses --- Superinformatique --- Réseaux d'ordinateurs --- Informatique --- Telecommunications --- Computer Science --- Engineering & Applied Sciences --- Electrical & Computer Engineering --- Données volumineuses --- Réseaux d'ordinateurs --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- HPC (Computer science) --- Data sets, Large --- Large data sets --- Computer science. --- Microprocessors. --- Computer communication systems. --- Application software. --- Computer Science. --- Computer Communication Networks. --- Information Systems Applications (incl. Internet). --- Computer Appl. in Administrative Data Processing. --- Processor Architectures. --- Electronic data processing --- Cyberinfrastructure --- Supercomputers --- Computers --- Office practice --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Network computers --- Automation --- Distributed processing --- Information systems. --- Informatics --- Science --- Data sets --- Minicomputers --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software


Digital
High-Performance Big-Data Analytics : Computing Systems and Approaches
Authors: --- --- ---
ISBN: 9783319207445 9783319207438 9783319207452 9783319363240 Year: 2015 Publisher: Cham Springer International Publishing

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Export citation

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Bookmark

Abstract

This important and timely text/reference presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Comprehensively covering a diverse range of computer systems and proven techniques for high-performance big-data analytics, the book also presents case studies, practical guidelines, and best practices for enabling decision-making toward implementing the appropriate computer systems and approaches. Topics and features: Includes case studies and learning activities throughout the book, and self-study exercises at the end of every chapter Presents detailed case studies on social media analytics for intelligent businesses, and on big data analytics in the healthcare sector Describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data Examines real-time analytics solutions, such as machine data analytics and operational analytics Introduces in-database processing and in-memory analytics techniques for data mining Discusses the use of mainframes for handling real-time big data, and the latest types of data management systems for big and fast data analytics Provides information on the use of cluster, grid and cloud computing systems for big data analytics and data-intensive processing Reviews the peer-to-peer techniques and tools, and the common information visualization techniques, used in big data analytics Software engineers, cloud professionals and big data scientists will find this book to be an informative and inspiring read, highlighting the indispensable role data analytics will play in shaping a smart future.

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