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Fakultät für Informatik

Marcel Altendeitering defends Doctoral Dissertation

Marcel Altendeitering with Christian Janiesch and Falk Howar after defending his doctoral dissertation Please provide a copyright notice

Data is a key asset in a digital society: we collect and use data today, for example, as the basis for machine learning, for automated decision-making in companies, and as the basis for research. The quality of data is a necessary prerequisite for the meaningful use of data. It is therefore essential to develop methods and tools for ensuring and analyzing data quality. 

The requirements in the area of data quality are evolving along with the software architecture and the development processes for applications (from individual, locally used relational data to distributed, complex data streams shared between companies). In modern approaches (e.g., data meshes), the quality of data is ensured by the developers of data products. Both, the quantity and the complexity of the data as well as the decentralization of management require tool support for the analysis and assurance of data quality.

This is where Marcel Altendeitering's dissertation makes a contribution: he uses empirical research, conducted in multiple case studies with industrial partners at Fraunhofer ISST, to investigate and establish design principles for such tools. The dissertation is based on a selection of Marcel's publications on this topic.