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Build a data platform to the industry-leading standards set by MicrosoftGÇÖs own infrastructure. In Data Engineering on Azure you will learn how to: * Pick the right Azure services for different data scenarios * Manage data inventory * Implement production quality data modeling, analytics, and machine learning workloads * Handle data governance * Using DevOps to increase reliability * Ingesting, storing, and distributing data * Apply best practices for compliance and access control Data Engineering on Azure reveals the data management patterns and techniques that support MicrosoftGÇÖs own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning.