Microsoft Azure has over 20 platform-as-a-service (PaaS) offerings
that can act in support of a big data analytics solution. So which
one is right for your project? This practical book helps you
understand the breadth of Azure services by organizing them into a
reference framework you can use when crafting your own big data
analytics solution. You'll not only be able to determine which
service best fits the job, but also learn how to implement a
complete solution that scales, provides human fault tolerance, and
supports future needs. Understand the fundamental patterns of the
data lake and lambda architecture Recognize the canonical steps in
the analytics data pipeline and learn how to use Azure Data Factory
to orchestrate them Implement data lakes and lambda architectures,
using Azure Data Lake Store, Data Lake Analytics, HDInsight
(including Spark), Stream Analytics, SQL Data Warehouse, and Event
Hubs Understand where Azure Machine Learning fits into your
analytics pipeline Gain experience using these services on
real-world data that has real-world problems, with scenarios
ranging from aviation to Internet of Things (IoT)
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