Martin Schoombee continues a series on orchestration in Azure Data Factory:
We’re finally ready to dive into the Data Factory components that form part of the framework, and we’re going to work our way from the bottom up. To paraphrase the previous blog post, worker pipelines perform the actual work of either moving data (from source to staging) or executing a stored procedure that will load a dimension/fact table.
Although worker pipelines can contain any number of tasks you may need, my worker pipelines that move data from a source system into the staging area follow a similar pattern with at least the following activities:
Click through for that list, as well as more information.