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Big Data for Chimps (Paperback)
Philip Kromer; Contributions by Russell Jurney
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R969
R706
Discovery Miles 7 060
Save R263 (27%)
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Ships in 12 - 17 working days
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Finding patterns in massive event streams can be difficult, but
learning how to find them doesn't have to be. This unique hands-on
guide shows you how to solve this and many other problems in
large-scale data processing with simple, fun, and elegant tools
that leverage Apache Hadoop. You'll gain a practical, actionable
view of big data by working with real data and real problems.
Perfect for beginners, this book's approach will also appeal to
experienced practitioners who want to brush up on their skills.
Part I explains how Hadoop and MapReduce work, while Part II covers
many analytic patterns you can use to process any data. As you work
through several exercises, you'll also learn how to use Apache Pig
to process data. Learn the necessary mechanics of working with
Hadoop, including how data and computation move around the cluster
Dive into map/reduce mechanics and build your first map/reduce job
in Python Understand how to run chains of map/reduce jobs in the
form of Pig scripts Use a real-world dataset-baseball performance
statistics-throughout the book Work with examples of several
analytic patterns, and learn when and where you might use them
Data science teams looking to turn research into useful analytics
applications require not only the right tools, but also the right
approach if they're to succeed. With the revised second edition of
this hands-on guide, up-and-coming data scientists will learn how
to use the Agile Data Science development methodology to build data
applications with Python, Apache Spark, Kafka, and other tools.
Author Russell Jurney demonstrates how to compose a data platform
for building, deploying, and refining analytics applications with
Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and
Apache Airflow. You'll learn an iterative approach that lets you
quickly change the kind of analysis you're doing, depending on what
the data is telling you. Publish data science work as a web
application, and affect meaningful change in your organization.
Build value from your data in a series of agile sprints, using the
data-value pyramid Extract features for statistical models from a
single dataset Visualize data with charts, and expose different
aspects through interactive reports Use historical data to predict
the future via classification and regression Translate predictions
into actions Get feedback from users after each sprint to keep your
project on track
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