This module will investigate the critical concepts required for architecting data workflows with Azure Data Factory. We will start by reviewing where Data Factory fits in a Lambda architecture. We will also define the phases of a data pipeline in Data Factory. Next, we will review the Data Factory architecture. This will include the various objects that make up a data factory pipeline along with how each of them fits together to form a pipeline. We will then do a deep dive into the copy activity which is the most commonly used activity. From there, we will look at bring-your own vs on-demand compute in a data pipeline ,and finally, we will tackle pipeline execution using manual, tumbling window, schedule and event based triggers.