Forum Discussion
How do I improve render speed?
Recognizing that none of the values to be displayed were reliant on filters or sliders I had already moved them all to columns. If I understand correctly, they should all be computed when the dataset is imported and not at render time.
That leaves me at option 1 - reduce the number of visualisations by spreading them out across multiple pages.
Quite a few of my reports have 10 to 12 visuals on them and all render fairly fast. The only exception is when i'm displaying graphs that have to calculation on many millions of rows of data. Without knowing your dataset I'm now quite curious what sort of data you are using and what visualisations you are creating using only calculated columns and still getting poor performance. I would have to imagine you either have a tonne of sizable tables with lots of complex relationships? Can you optimise your dataset in anyway instead?
General best practise is that if you have a choice between a calculated column and a measure, the measure should be your first choice. I would be concerned if you feel you need to shy away from them.
The report is more of an infographic, with big number showing aggregates (revenue this week or month) and aggregates of aggregates (best week in the past 3 months, in terms of revenue). There are no visualistions that provide filering or drill down.
I have 2 versions of the report: measures, and columns.
For the columns report I again have 2 versions: fancy visualisations, and simple tables.
The columns-tables version is rendering in a second or so, but that's not the task. The task is to provide fancy visualisation that are just as effective on mobile as desktop. To that end I think I'm using a rather heavy visualisation (Infographic Designer) to put numbers and text inside shapes because the Card visualisation is too simple.
I'm not curious how you are calculating some of these figures, specificly the ones like "Best week in past 3 months" without using a measure? This would be a perfect calculation for dax to complete quickly.
Is your data model fairly sizable with lots of tables and columns? Could we leverage power query or a tabular model in the data source to create some mini tables to pre-calculate things like Weekly Revenue?
Maybe I'm using some of the wrong terminology, and I apologise.
I originally created the calculations as measures using DAX within the Reports View of Power BI Desktop.
I recreated them as summary tables in the Data View. This is Power Query, right? This is what I've been refering to as "columns" since they are both precomputed.
I don't know what the definition of large is, but I'm still concerned about the speed difference between presenting the summary table as a grids (near instant) vs displaying it with a tachomoters (22sec).