"Principles of Big Data" helps readers avoid the common mistakes
that endanger all Big Data projects. By stressing simple,
fundamental concepts, this book teaches readers how to organize
large volumes of complex data, and how to achieve data permanence
when the content of the data is constantly changing. General
methods for data verification and validation, as specifically
applied to Big Data resources, are stressed throughout the book.
The book demonstrates how adept analysts can find relationships
among data objects held in disparate Big Data resources, when the
data objects are endowed with semantic support (i.e., organized in
classes of uniquely identified data objects). Readers will learn
how their data can be integrated with data from other resources,
and how the data extracted from Big Data resources can be used for
purposes beyond those imagined by the data creators.
Learn general methods for specifying Big Data in a way that is
understandable to humans and to computers.
Avoid the pitfalls in Big Data design and analysis.
Understand how to create and use Big Data safely and
responsibly with a set of laws, regulations and ethical standards
that apply to the acquisition, distribution and integration of Big
Data resources. "
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