The extraction of valuable information from systematic errors is the key to progress in crystallography as they
convey not only errors in the structure model, but also methodological problems in data acquisition and data processing protocols, in protocols of data quality evaluation itself, in models of diffraction, extinction, absorption
etc., as well as in software for hardware like detectors. Concrete examples are given to demonstrate what data quality evaluation as developed by DataQ Intelligence
is capable of doing even without knowing all the technical details.