Best Of

I think that you would need to restructure your data. If you had something like this:

Then you could create some filter cards for each of the ServiceNames. If you wanted only entities with both service A and C, then you would filter for `ServiceName A` = 'x' and `ServiceName C` = 'x'

@MattLynn You can also do this through and ETL if you don't care about filtering/drilling. You can just split your dataset and create a separate 'table' for each metric, and do the 2021 and 2022 values, and % Change for each one, and then append them all and create your card off the new dataset.

@MattLynn I think that you will be best served by splitting this table into multiple tables. One for case load by source, one for Resolution method, and one for Customer Experience.

I'm not sure how your data is structured, but I took a stab at the first table (case load by source). The part that I stumbled on here was that your summary value is the total case volume while the rest of the values are displayed as a percent of that total. I chose to include both on my table:

Here are some of the beastmodes that I wrote, but these may not work for your dataset. It might be easier if you shared a bit of the data behind this request so that someone can try to provide a more concrete solution.

2021 Qty

SUM(CASE WHEN `Year`=2021 THEN `Quantity` ELSE 0 END)

Qty % Change

(SUM(CASE WHEN `Year`=2022 then `Quantity` ELSE 0 END) - SUM(CASE WHEN `Year`=2021 THEN `Quantity` ELSE 0 END))
/
SUM(CASE WHEN `Year`=2021 THEN `Quantity` ELSE 0 END)

2021 %

sum(case when `Year`=2021 then `Quantity` END) / sum(sum(case when `Year`=2021 then `Quantity` END)) over ()

% Change

((100*sum(case when `Year`=2022 then `Quantity` else 0 END) / sum(sum(case when `Year`=2022 then `Quantity` else 0 END)) over () )
 - (100*sum(case when `Year`=2021 then `Quantity` else 0 END) / sum(sum(case when `Year`=2021 then `Quantity` else 0 END)) over ())
)
/
(100*sum(case when `Year`=2021 then `Quantity` else 0 END) / sum(sum(case when `Year`=2021 then `Quantity` else 0 END)) over ())

I'm not sure how helpful this will be, as I probably do not have the same schema as your dataset, but I hope this helps.

Hi @svetlana

You could always use a Pie or Donut Chart. Just in the General Chart Properties enter 3 as the maximum slices:

You can even get more details on the "Other" category by just moving your mouse over that pie piece: