Institutional Research (IR) in universities needs data from many different systems, but it is often hard to know what data is stored and where. To solve this, it is important to design both databases and business processes together. In this study, categorical databases, ontology logs (ologs), and event-driven process chains (EPCs) are used to connect institutional documents with data and process design. Ologs describe concepts and their functional relations in a formal but also readable way, while EPCs show how events and functions go step by step in the real processes. Generative AI was used to support both tasks. The AI helps to read documents, to extract concepts and functions, and to check consistency. By comparing ologs and EPCs, both sides can be improved and give a unified view of data and processes. This makes it possible to design information systems for IR with more consistency and less effort.