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Large scale and big data : processing and management / edited by, Sherif Sakr, Mohamed Medhat Gaber.

Contributor(s): Material type: TextPublication details: Boca Raton : CRC Press Taylor & Francis Group c2016Description: xiii, 622 pages : illustrations ; 24 cmISBN:
  • 9781138033948 (hardback)
Subject(s): DDC classification:
  • 005.7 23
LOC classification:
  • QA76.9.D3 L3667 2016
Other classification:
  • COM021000 | COM021030 | COM051230
Summary: "This book provides a central source of reference on the various data management techniques of large scale data processing and its technology application. This book presents chapters written by leading researchers, academics, and practitioners in the field, all of which have been reviewed by independent reviewers. The book covers the latest research discoveries and applications. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques"--
Item type: Books
Holdings
Cover image Item type Current library Home library Collection Shelving location Call number Materials specified Vol info URL Copy number Status Notes Date due Barcode Item holds Item hold queue priority Course reserves
Judith Thomas Library General Stacks Books QA 76.9 .D3 L3667 2016 (Browse shelf(Opens below)) AUA25001 Available AUA25001

Includes bibliographical references and index.

"This book provides a central source of reference on the various data management techniques of large scale data processing and its technology application. This book presents chapters written by leading researchers, academics, and practitioners in the field, all of which have been reviewed by independent reviewers. The book covers the latest research discoveries and applications. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques"--