Mastering Azure Analytics

Architecting in the Cloud with Azure Data Lake, HDInsight, and Spark

Nonfiction, Computers, Database Management, Data Processing, Programming
Cover of the book Mastering Azure Analytics by Zoiner Tejada, O'Reilly Media
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Author: Zoiner Tejada ISBN: 9781491956601
Publisher: O'Reilly Media Publication: April 6, 2017
Imprint: O'Reilly Media Language: English
Author: Zoiner Tejada
ISBN: 9781491956601
Publisher: O'Reilly Media
Publication: April 6, 2017
Imprint: O'Reilly Media
Language: English

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)
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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