As we know, Process Mining has the tremendous advantage of providing an objective and realistic view on the processes, as opposed to the traditional BPM analysis, which is very dependent on human judgement and prone to bias.
However, building a process model from an event log is not a straightforward task. It requires an algorithm, and algorithms are based on assumptions have to somehow deal with things like noise. Conformance checking can also be done in different ways.
Therefore, to better understand my results, I would be very interested in learning the algorithms used by Celonis. Thanks!