Data structure for tableau: replace only some rows (dates) via filter for n number of cases/scenarios

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I am using Tableau Desktop and Tableau Prep. In best case I can solve this issue in Prep to optimize the dashboard performance (and Prep is able to execute custom SQL for instance). Nevertheless: if there is an easy solution in Tableau Desktop this might work as well.

Overall goal:

Visualize all project-requests per pool over time. Include several scenarios per pool.

Data source "Requests":

Date ProjectID Pool Request
March 25 6234 PoolA 1
April 24 92345 PoolB 0,5
April 23 123 PoolB 0,5

Data source "Scenarios":

Date ProjectID Pool Scenario
March 26 6234 PoolA rabbit
April 22 92345 PoolB duck

Restrictions:

  • Key is ProjectID
  • len(Requests) >>> len(Scenarios)
  • "Scenario" will only replace some request-dates. To check the complete simulated overview, you need to include replaced rows but also some original rows per pool
  • Number of scenarios is dynamic and not fixed
  • Several scenarios might replace/affect the very same row from "Requests"
  • To avoid conflicts its just possible to select one scenario

Questions:

  • Whats the most elegant data structure to visualize this data and these scenarios in Tableau?
  • One solution: dont join but concatenate and use one filter to "activate" the scenario and another filter to "deactivate" the just replaced rows. Bad from a user perspective (two filters for just one scenario)
  • Brute force: duplicate every row per scenario (updated rows AND untouched rows). Should work in theory but will blow up my table even more
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