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Big Data
Principles and Paradigms
Explains the key algorithms, tools, technologies, and best practices that enable Big Data platforms for numerous scientific, business, and consumer applications
Rajkumar Buyya (Edited by), Rodrigo N. Calheiros (Edited by), Amir Vahid Dastjerdi (Edited by)
9780128053942, Elsevier Science
Paperback, published 9 June 2016
494 pages
23.4 x 19 x 3.1 cm, 1.04 kg
Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications. To help realize Big Data’s full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues.
Part I: Big Data Science Part II: Big Data Infrastructures and Platforms Part III: Big Data Security and Policy Part IV: Big Data Applications
Subject Areas: Databases [UN], Information technology: general issues [UB], Library, archive & information management [GLC]
