Analysis <-> ML interaction

Hi all,

Our use case:
We would like to allow our end-users of the Celonis analyses to test hypotheses themselves (does attribute X correlate with KPI y?).

As we are currently still on-premise we are investigating connecting Celonis to an R-Server to enable the RCALL function. This would allows us to dynamically build the data set to pass to R and then present the result in a user-friendly way.

However, as we might move to the IBC in the (near or far) future, we wondering if such analysis <-> ML interaction is also possible with the ML Workbench. Concretely, can we pass parameters from the analysis to a stored ML function/notebook which then returns the results to be presented in the analysis?
An alternative would be to pre-calculate every possible combination of attribute (sets) and KPIs, which I guess is not handy.

Looking forward to some inspiration!


Hi Joos,
yes, we are releasing an ML component for the Analysis soon! If you want, you can try it out already on the IBC. Happy to get your feedback on it.
I will follow up with you via email.

1 Like