Azure Data Engineering teaches you how to design a reliable, performant, and cost-effective data infrastructure in Azure by progressively building a complete working analytics system.

Readers should be comfortable with RDBMS systems like SQL Server and scripting using a language like PowerShell, Bash, or Python. Book examples use PowerShell and C#.

The Microsoft Azure cloud is an ideal platform for data-intensive applications. Designed for productivity, Azure provides pre-built services that make collection, storage, and analysis much easier to implement and manage.

The Microsoft Azure cloud platform can host virtually any sort of computing task, from simple web applications to full-scale enterprise systems. With many pre-built services for everything from data storage to advanced machine learning, Azure offers all the building blocks for scalable big data analysis systems including ingestion, processing, querying, and migration.

- Azure cloud services architecture

- Building a data warehouse in Azure

- How to choose the right Azure technology for your task

- Calculating fixed and variable costs

- Hot and cold path analytics

Richard Nuckolls is a senior developer building a big data analytics and reporting system in Azure. During his nearly 20 years of experience, he's done server and database administration, desktop and web development, and more recently has led teams in building a production content management system in Azure.