Data mining refers to the recognition of patterns and structures in large data sets. Information is generated, for example on similarities, deviations or anomalies, as well as mathematical-statistical models and algorithms that can be used in new situations with the same facts in order to at least support decisions. Data mining is considered to have an enormous innovation potential in almost all areas of life. However there are concerns about non-transparent procedures as well as unequal possibilities of making us of data mining. Involved fears refer to, e.g. an end of privacy or the uncontrollability of algorithmic systems. Among others, there are challenges with regard to providing data, specifying the possibilities and limits of the analysis, and dealing with the results. Extensive expertise is required for implementation, verification and monitoring. Impact assessments and evaluations should be based on the respective application. (The TAB report of the same name, available only in German) discusses examples for data mining in the fields of medicine and healthcare.)