Data Engineering on Azure

Build a data platform to the industry-leading standards set by Microsoft’s own infrastructure.
Summary
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 Microsoft’s 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.