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Books > Computing & IT > Computer communications & networking
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Demystifying Graph Data Science - Graph algorithms, analytics methods, platforms, databases, and use cases (Hardcover)
Loot Price: R3,010
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Demystifying Graph Data Science - Graph algorithms, analytics methods, platforms, databases, and use cases (Hardcover)
Series: Computing and Networks
Expected to ship within 18 - 22 working days
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With the growing maturity and stability of digitization and edge
technologies, vast numbers of digital entities, connected devices,
and microservices interact purposefully to create huge sets of
poly-structured digital data. Corporations are continuously seeking
fresh ways to use their data to drive business innovations and
disruptions to bring in real digital transformation. Data science
(DS) is proving to be the one-stop solution for simplifying the
process of knowledge discovery and dissemination out of massive
amounts of multi-structured data. Supported by query languages,
databases, algorithms, platforms, analytics methods and machine and
deep learning (ML and DL) algorithms, graphs are now emerging as a
new data structure for optimally representing a variety of data and
their intimate relationships. Compared to traditional analytics
methods, the connectedness of data points in graph analytics
facilitates the identification of clusters of related data points
based on levels of influence, association, interaction frequency
and probability. Graph analytics is being empowered through a host
of path-breaking analytics techniques to explore and pinpoint
beneficial relationships between different entities such as
organizations, people and transactions. This edited book aims to
explain the various aspects and importance of graph data science.
The authors from both academia and industry cover algorithms,
analytics methods, platforms and databases that are intrinsically
capable of creating business value by intelligently leveraging
connected data. This book will be a valuable reference for ICTs
industry and academic researchers, scientists and engineers, and
lecturers and advanced students in the fields of data analytics,
data science, cloud/fog/edge architecture, internet of things,
artificial intelligence/machine and deep learning, and related
fields of applications. It will also be of interest to analytics
professionals in industry and IT operations teams.
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