Forum Discussion
PC advise Specification for Developing Dashboards for "Big Data" multiple DAX codes
Hi PowerBI_LOVER,
Even if you go for the service the refresh of 100m rows will take longer than 30 minutes specially if you are trying to do a lot of transformations and tables using dax.
If you are trying to load 100m rows to desktop has I referred previously has a best practice you should not do that.
The dax measures have no impact in terms of refresh since they are only calculated at the time you called them on your visuals.
Altough I understand what you want to achieve with this type of configuration large semantic model should be setup with only part of the data and then push the refresh to the service.
On top of this having this large semântica models you also should consider the usage of incremental refresh or aggregation tables, this will reduce the refresh time but also the performance when building your reports.
Hi PowerBI_LOVER ,
Not sure where you got this setup and number of rows comparision, but I can tell you from experience that I have worked with models with up to 100 Millions rows with a computer with 32GB of ram and an I7.
This is not only dependent on the computer performance, but also on the way you built your model and the calculations you do.
Off course that if you are working with millions of lines the loading time can take some time but not the dax.
However has a best practice if you have models with 10M rows I would not load everything into Power BI I would use some paremeters to crop the data and then on the service would do the full refresh.
For the DAX measures depending on what you are doing I also suggest to use external tools (tabular editor) to avoid the waiting time when you do the OK on the dax formula bar.