Researchers are not only searching for relevant data but also for relevant algorithms to be able to investigate novel topics. As analytical implementations and achieved performance are not consistently reported, it can be extremely challenging to choose a suitable approach for specific research questions, which severely inhibits scientific progress. To make data useful for research applications, BERD@NFDI will provide access to analytical capabilities that can be applied across various data sets. This will allow researchers to build on prior work, both in terms of data and analytical capability. It will also reduce redundant efforts across research units and address the demands of responsible AI. BERD@NFDI enables users to assess algorithmic performance both for data on BERD@NFDI and for their own data to quickly understand potential novel applications, as well as performance differences across applications of interest. Data storage, computing capacity, and analytical capabilities will be provided in one central infrastructure and will be complemented by algorithm repositories. Moreover, the infrastructure will support the enrichment and linking of data. Based on an ontology for business and economic data, a semantic network will be developed to capture complex relationships between companies and their social and historical environments.