Hi,
I created a dataflow to load 6 dimensions in Dataverse tables from flat files (csv) dropped by users into a Teams SharePoint directory. 4 dimensions are very slow changing, they need updates from twice a year to only once every 2 years. The other 2 dimensions would benefit from a daily or at least weekly update.
Whether the dataflow is scheduled, triggered manually or by Power Automate (I hope this will be possible soon), the problem is that not all 6 dimensions have to be updated and some source files are missing. Hence the dataflow constantly fails!
I temporarily fixed the problem by removing the part of the process that moves the csv files to the archive after they have been loaded, and by asking users to overwrite existing files when they move them to the drop-in folder in Teams. Then the dataflow always loads all 6 dimensions with old and new files. I find this solution hideous! For many reasons.
Is there a way to skip queries inside a dataflow when their source file is missing?
Can anybody suggest a better design?
Am I even using the right product?? I mean, dataflows work well for a one-shot data import but I’ve been struggling, and honestly very disappointed, with the data integration capabilities of dataflows to replicate standard ETL processes. In my opinion it’s still far away from SSIS!
Thank you
--mo