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

For storing, processing, and analyzing data of varying ingest speeds, shapes, and sizes, Microsoft Azure provides more than 25 platform-as-a-service options for implementing an analytics data pipeline. How do you choose the right options for your organization? This practical book provides a hands-on reference framework for crafting your own big data analytics solution with Azure. Author Zoiner Tejada introduces you to the fundamental architectural concepts, such as data lakes and lambda architecture, and then walks you through code samples for each stage of the analytics data pipeline. To help you select and apply Azure services at each stage, Tejada includes a case study scenario that spans the entire book, and provides real-world context to the code samples provided for every Azure service covered. Understand how to store your data at hyperscale, Design and implement solutions that deliver "hot" query results quickly and "cold" results accurately, Process data in batches, and handle streaming data in real-time microbatches or tuple-at-a-time ways, Integrate machine learning into your data pipeline, Manage, govern, and secure your data assets, Work with code samples in C#, Scala, and Java, languages native to services used in a modern analytics data pipeline Book jacket.