Learn Big Data from the ground up with this complete and up-to-date
resource from leaders in the field Big Data: Concepts, Technology,
and Architecture delivers a comprehensive treatment of Big Data
tools, terminology, and technology perfectly suited to a wide range
of business professionals, academic researchers, and students.
Beginning with a fulsome overview of what we mean when we say, "Big
Data," the book moves on to discuss every stage of the lifecycle of
Big Data. You'll learn about the creation of structured,
unstructured, and semi-structured data, data storage solutions,
traditional database solutions like SQL, data processing, data
analytics, machine learning, and data mining. You'll also discover
how specific technologies like Apache Hadoop, SQOOP, and Flume
work. Big Data also covers the central topic of big data
visualization with Tableau, and you'll learn how to create scatter
plots, histograms, bar, line, and pie charts with that software.
Accessibly organized, Big Data includes illuminating case studies
throughout the material, showing you how the included concepts have
been applied in real-world settings. Some of those concepts
include: The common challenges facing big data technology and
technologists, like data heterogeneity and incompleteness, data
volume and velocity, storage limitations, and privacy concerns
Relational and non-relational databases, like RDBMS, NoSQL, and
NewSQL databases Virtualizing Big Data through encapsulation,
partitioning, and isolating, as well as big data server
virtualization Apache software, including Hadoop, Cassandra, Avro,
Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle,
including business case evaluation, data preparation, extraction,
transformation, analysis, and visualization Perfect for data
scientists, data engineers, and database managers, Big Data also
belongs on the bookshelves of business intelligence analysts who
are required to make decisions based on large volumes of
information. Executives and managers who lead teams responsible for
keeping or understanding large datasets will also benefit from this
book.
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