Pivot Table summary values

Thanks friends!@Ashleigh I'm sorting on a beast mode but doesn't look like it removing it made much difference :(

@RobSomers It is pretty large... the dataset has 5.5M. When I apply filters to the pivot table card, it brings it down to about 10k. Do filters not help with "reducing the size"? What's weird is that it was working until I added a beast mode to filter out parts of the dataset

For context, the use case is to look at snapshots of a SFDC object on any given day. Ideally, we can view the trend in a bar/line chart and use a pivot table to see the $ breakout and drill down to which deals were forecasted on which date

@RobSomers

A colleague recommended I move the transform to MagicETL so it's a formula card now instead of a beast mode.

The transform is a bit confidential so can't really share the exact statement. In essence, it adds a column to pull through existing $ value for each record depending on 3/4 sets of criteria

Hopefully this is enough?

CASE WHEN `Stage`='7'

   THEN $

WHEN `Record Type` IN ('A','B') 

   AND `Stage` NOT LIKE '%7%'

   AND `Score`>= #

   AND DATEDIFF(`Snapshot Date`,`Last Modified Date`)<= #

   THEN `$`

  WHEN `Record Type` IN ('A','B') 

   AND `Score` IS NULL

   AND `Stage` NOT LIKE '%7%'

   AND ((`Stage`='1' AND `Days in Current Stage`<=#) OR 

      (`Stage`='2' AND `Days in Current Stage`<=#) OR

      (`Stage`='3' AND `Days in Current Stage`<=#) OR

      (`Stage`='4' AND `Days in Current Stage`<=#) OR

      (`Stage`='5' AND `Days in Current Stage`<=#) OR

      (`Stage`='6' AND `Days in Current Stage`<=#))

   THEN `$`

  WHEN `Record Type` IN ('C','D')

   AND `Score`>#

   AND `Stage` NOT LIKE '%7%'

   THEN `$`*#

  WHEN `Record Type` IN ('C','D')

   AND `Score`<=# AND `Score`>#

   AND `Stage` NOT LIKE '%7%'

   THEN `$`*#

  WHEN `Record Type` IN ('C','D')

   AND `Score`<=50 OR `Score` IS NULL

   AND `Stage` NOT LIKE '%7%'

   THEN `$`*#

  END