Given the events modeled by a business process, it may happen in the presence of alternative execution paths that the data required by a certain event determines somehow what event is executed next. Then, the process can be modeled by using an approximate functional dependency between the data required by both events. We apply this approach in the context of conformance checking: given a business process model with a functional dependency (FD) that no longer corresponds to the observed reality, we propose corrections to the FD to make it exact or at least to improve its confidence and produce a more accurate model.