Welcome to week 3!
Last week we discussed the core challenge of process mining: how to get from event data to process models.
This week we discuss what we can do when we combine the event data with a process model. Note that this process model can be discovered by an algorithm, but can also be provided as a ‘normative’ model (for instance used to configure the system).
We show how we can detect where the event data and process model agree, and where they don’t. We also discuss how we can project timing information onto process models. In this week we also show how social networks, e.g. how people collaborate within a process, can be discovered.
We also show several process mining case studies, so that you get a feeling of what else is possible with event data and process mining. Finally we also discuss several process mining activities and when these can be applied.
Next week we will apply the algorithms and tools discussed on real data.