I am working on a function to clean and optimize multiple delta tables in a lakehouse. Do we OPTIMIZE before VACis UUM or there other way around? Which one is the best approach?

Our team needs a little DAX help from any experts out there... We are looking to do for each row a trailing avg for prev 12 weeks for a metric lifts per hour = successful lifts / time on clock. I attached an image of the grid and put in what our DAX query looks like at the moment. Code: Trailing_12_Week_Avg_Lifts_Per_Hour = var CurrentDate = MAX(dim_date[event_date]) var PreviousDate = CurrentDate - 84 var Result = CALCULATE( [lifts_per_hour], DATESINPERIOD( dim_date[event_date], MAX(dim_date[event_date]), -84, DAY ) ) RETURN Result Any assistance would be appreciated!

So, apparently I have been trying to ingest over 7 million rows from an API to a lakehouse table using a notebook, and due to rate limiting, it has taken quite a while (more than expected). Two challenges: 1. "Failed to render content" screen whenever I try to access the pipeline while it runs. 2. The pipeline times out after 12 hours Is this normal?

Hello, I was just wondering how people manage their study time between work and family. Do you study before/after work, maybe you study in the evening til quite late after putting the kids to bed? Do you stay late at work and study after hours before going home? How do you deal with the frustration of not getting in any study for a few days because of life commitments? Do you have an arrangement with your family that study time is study time? I'd be really interested in how any of you shape or organise your busy lives around study time.

Hi folks, having quite a few errors with G2 Dataflows, even when using a .pqt and importing the exact G1 df to a G2 its failing substantially, Ive been trying a bunch of stuff with switching of Fast copy/Enable Staging, and writing to a LH or not, even when its at its most simple form it seems to fail. Granted there is a bit going on in this DF, originally it was 4 merges in each of 2 queries and then a join. Ive moved half to a notebook but there still seems to be considerable issues and differences, just wondering if others are experiencing the same issues? my final state will move all of the transform to a NB, but surely DF's should still perform as G1! Similar issues: https://community.fabric.microsoft.com/t5/Service/Dataflow-Gen2-Issue/m-p/3275868 https://community.fabric.microsoft.com/t5/Dataflow/Couldn-t-refresh-the-entity-because-of-an-issue-with-the-mashup/m-p/3506887 https://community.fabric.microsoft.com/t5/Dataflow/Gen2-Dataflow-Failed-to-insert-a-table/m-p/3372458 Additional questions: do Dataflows use Datafactory in the background? this would make sense if the schemas are not perfect, it needs the same treatment as delta schema rules etc. why cant the errors be more helpful?! Cheers Ross