Distributed Computing In Big Data Analytics: Concepts, Technologies And Applications (scalable Computing And Communications)
by Ganesh Chandra Deka /
2017 / English / EPUB
3.1 MB Download
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.
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.
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.
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.