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Mathematics of Big Data - Spreadsheets, Databases, Matrices, and Graphs (Hardcover)
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Mathematics of Big Data - Spreadsheets, Databases, Matrices, and Graphs (Hardcover)
Series: MIT Lincoln Laboratory Series
Expected to ship within 9 - 15 working days
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The first book to present the common mathematical foundations of
big data analysis across a range of applications and technologies.
Today, the volume, velocity, and variety of data are increasing
rapidly across a range of fields, including Internet search,
healthcare, finance, social media, wireless devices, and
cybersecurity. Indeed, these data are growing at a rate beyond our
capacity to analyze them. The tools-including spreadsheets,
databases, matrices, and graphs-developed to address this challenge
all reflect the need to store and operate on data as whole sets
rather than as individual elements. This book presents the common
mathematical foundations of these data sets that apply across many
applications and technologies. Associative arrays unify and
simplify data, allowing readers to look past the differences among
the various tools and leverage their mathematical similarities in
order to solve the hardest big data challenges. The book first
introduces the concept of the associative array in practical terms,
presents the associative array manipulation system D4M (Dynamic
Distributed Dimensional Data Model), and describes the application
of associative arrays to graph analysis and machine learning. It
provides a mathematically rigorous definition of associative arrays
and describes the properties of associative arrays that arise from
this definition. Finally, the book shows how concepts of linearity
can be extended to encompass associative arrays. Mathematics of Big
Data can be used as a textbook or reference by engineers,
scientists, mathematicians, computer scientists, and software
engineers who analyze big data.
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