  Much time in process mining projects is spent on finding and understanding
data sources and extracting the event data needed. As a result, only a fraction
of time is spent actually applying techniques to discover, control and predict
the business process. Moreover, there is a lack of techniques to display
relationships on top of databases without the need to express a complex query
to get the required information. In this paper, a novel modeling technique that
works on top of databases is presented. This technique is able to show a
multigraph representing activities inferred from database events, connected
with edges that are annotated with frequency and performance information. The
representation may be the entry point to apply advanced process mining
techniques that work on classic event logs, as the model provides a simple way
to retrieve a classic event log from a specified piece of model. Comparison
with similar techniques and an empirical evaluation are provided.
