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)

About the Author:

Zoiner is CEO at Solliance, a Microsoft MVP, a Microsoft Certified Solution Developer (MCSD), and an advisor to several teams at Microsoft.He is passionate about leveraging cloud technologies to build web-based solutions that run at scale, and enjoys engaging the greater community by speaking at conferences and user group meetings. Zoiner creates and teaches related online courses at the University of California San Diego (UCSD), and has co-authored various publications on Microsoft's Windows Azure and Office 365. He is also a contributing columnist to DevPro magazine s All About Azure. Zoiner has a degree in computer science from Stanford University."

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