Maintaining a functional set of knowledge on the breadth and depth of Azure Data Platform resources is hard. There is now so many different ways to execute many different data processing workloads on many different flavours of compute and storage. What should we use, and when? It depends is common answer! However, in this full data of training help is at hand. We will cover the A-Z of (data engineering focused) Azure Data Resources, yes, its depends, but we'll go deeper and learn what it depends on. From the perspective of an experienced solution architect and based on real world implementations, we'll address what to use, when to use it, why and how. Including tips and tricks for the deployment of resources into production along the way. To support this understanding we'll cover a set of use case driven scenarios and the various resources/architecture patterns used to implement them.