The obvious and easy reason for having multiple Data Factory’s could be that you simply want to separate your business processes. Maybe they all have separate data delivery requirements and it just makes management of data flows easier to handle. For example:
They could have different data delivery deadlines, they process on different schedules and don’t share any underlying connections.
You may also have multiple projects underway that mean you want to keep teams isolated.
But that’s not the only reason, so click through to learn several other reasons why you might have multiple Azure Data Factory instances running.