In order to reveal confidential information, a data intruder has several alternatives. One of these is the so-called database cross match, where it is tried to assign as many records as possible - belonging to the same entity - of an external database (the intruder’s additional knowledge) to the target data. In a heuristic has been proposed for these purposes to be implemented in the next update of the software package m-Argus. In the present paper we study the algorithm’s output after application to the German turnover tax statistics as target data. Moreover, we give a detailed overview of the results obtained by different parameter settings of the algorithm, in particular we analyze the effects of the categorical key variables contained in both external and target data. The application gives an approach to generate anonymised confidential data to be disseminated to the scientifical community.