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  • Big Data Management and Processing

    Big Data Management and Processing by Li, Kuan-Ching; Jiang, Hai; Zomaya, Albert Y.;

    Series: Chapman & Hall/CRC Big Data Series;

      • GET 20% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice GBP 44.99
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        21 493 Ft (20 470 Ft + 5% VAT)
      • Discount 20% (cc. 4 299 Ft off)
      • Discounted price 17 195 Ft (16 376 Ft + 5% VAT)

    21 493 Ft

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    Availability

    Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
    Not in stock at Prospero.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Short description:

    This book aims to bridge the gap between large amounts of data and appropriate computational and management methods for scientific discovery. It explores technologies for media/data communication, elastic media/data storage, and cross-network media/data fusion.

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    Long description:

    From the Foreword:



    "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies."



    ---Sartaj Sahni, University of Florida, USA



    "Big Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students, researchers and seasoned practitioners in Big Data fields.



    --Hai Jin, Huazhong University of Science and Technology, China



    Big Data Management and Processing explores a range of big data related issues and their impact on the design of new computing systems. The twenty-one chapters were carefully selected and feature contributions from several outstanding researchers. The book endeavors to strike a balance between theoretical and practical coverage of innovative problem solving techniques for a range of platforms. It serves as a repository of paradigms, technologies, and applications that target different facets of big data computing systems.





    The first part of the book explores energy and resource management issues, as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co-scheduling for high performance computing applications. The second part of the book includes comprehensive coverage of Hadoop and Spark, along with security, privacy, and trust challenges and solutions.





    The latter part of the book covers mining and clustering in Big Data, and includes applications in genomics, hospital big data processing, and vehicular cloud computing. The book also analyzes funding for Big Data projects.

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    Table of Contents:



    Big Data Management. Big Data Design, implementation, evaluation and services. Big Data as integration of technologies. Big Data analytics and visualization. Query processing and indexing. Elasticity for data management systems. Self-adaptive and energy-efficient mechanisms. Performance evaluation. Security, privacy, trust, data ownership and risk simulations. Processing. Techniques, algorithms and innovative methods of processing. Business and economic models. Adoption cases, frameworks and user evaluations. Data-intensive and scalable computing on hybrid infrastructures. MapReduce based computations. Many-Task Computing in the Cloud. Streaming and real-time processing. Big Data systems and applications for multidisciplinary applications.

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