Principles of Big Data helps readers avoid the common mistakes that
endanger all Big Data projects. By stressing simple, fundamental
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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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