The goal of DaCoMo is to develop a novel, totally data driven process for predictive maintenance which needs no prior knowledge of the machine itself or its components in order to detect and predict faults. This increases the efficiency of the service: neither frequency spectra need to be input nor visually inspected by experts. The challenge lies in the acquisition of data sets with representative error signatures and in learning the fault characteristics purely from data.