Forum Discussion
Filter Table using slicer
SUMMARIZE is a function to group the data, reducing the amount of data in the rows and using aggregate functions to summarize some columns. You can filter out data as you have found, although CALCULATE is the best method for filtering data in a measure.
Alternatively if you want to slice on the grouped table you should create a Calculated Table (Modeling > New Table) e.g.
SUMMARIZECOLUMNS( 'Data-2024'[Country], 'Data-2024'[Company], 'Data-2024'[Product], "Total Sales", SUM('Data-2024'[Sales]) )For the slicer, just select select the slicer visual and drop the Company column onto the visual.
If you use the Table visual, then you might find that you get the desired result by just dragging columns from 'Data-2024' table onto the visual, with the Sales column being the last one. The latter will create a implicit measure and sum the sales for each country x company x product. You don't then need the summary table per above.
SUMMARIZE is a function to group the data, reducing the amount of data in the rows and using aggregate functions to summarize some columns. You can filter out data as you have found, although CALCULATE is the best method for filtering data in a measure.
Alternatively if you want to slice on the grouped table you should create a Calculated Table (Modeling > New Table) e.g.
SUMMARIZECOLUMNS(
'Data-2024'[Country],
'Data-2024'[Company],
'Data-2024'[Product],
"Total Sales", SUM('Data-2024'[Sales])
)
For the slicer, just select select the slicer visual and drop the Company column onto the visual.
If you use the Table visual, then you might find that you get the desired result by just dragging columns from 'Data-2024' table onto the visual, with the Sales column being the last one. The latter will create a implicit measure and sum the sales for each country x company x product. You don't then need the summary table per above.