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Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use.
This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations.
Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies.
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Distributed Computing in Big Data Analytics (Scalable Computing and Communications)
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Springer, 2017
ISBN 10: 3319598333
ISBN 13: 9783319598338
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Distributed Computing in Big Data Analytics : Concepts, Technologies and Applications
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Springer International Publishing, 2017
ISBN 10: 3319598333
ISBN 13: 9783319598338
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Distributed Computing in Big Data Analytics
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Springer International Publishing Sep 2017, 2017
ISBN 10: 3319598333
ISBN 13: 9783319598338
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use.This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations. Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies. 172 pp. Englisch. Codice articolo 9783319598338
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Distributed Computing in Big Data Analytics (Scalable Computing and Communications)
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Distributed Computing in Big Data Analytics : Concepts, Technologies and Applications
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Distributed Computing in Big Data Analytics (Scalable Computing and Communications)
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Distributed Computing in Big Data Analytics : Concepts, Technologies and Applications
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Distributed Computing in Big Data Analytics (Hardcover)
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Springer International Publishing AG, Cham, 2017
ISBN 10: 3319598333
ISBN 13: 9783319598338
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Hardcover. Condizione: new. Hardcover. Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use.This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations. Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use.This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9783319598338
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