Which Azure Data Factory component is used to run data ingestion tasks?

In Azure Data Factory, pipelines are the primary components used to orchestrate and manage data workflows. A pipeline can contain a sequence of activities, which represent the tasks that need to be executed, including data ingestion tasks.

When you want to move data from a source to a destination, you define the steps of this movement in a pipeline. Each pipeline can run one or multiple activities, such as copying data from one place to another, transforming that data, or even executing external processing tasks. The pipeline is responsible for managing the flow of these activities, enabling you to schedule and monitor your data ingestion processes effectively.

While activities are indeed the tasks within a pipeline, they do not operate independently or execute without the context of a pipeline. Triggers are used to define the schedule for when a pipeline runs, and dataflows are more focused on transforming data rather than solely on data ingestion. Thus, pipelines are the correct answer as they encompass the entire data ingestion workflow, including the execution of the tasks required to move data.