An important strategy for companies to enhance their competitiveness is the extraction of information from operational data. Existing systems are either optimized for operational or for decision-making data processing. However, the incompatibility of current business data with historical business analyses makes the information extraction processes costly and time-consuming. Pascal Schmidt-Volkmar investigates whether the distinction between operational and decision-making data processing can be resolved. He develops the concept of a main memory-based system that supports both types of systems. Through a prototype, he demonstrates its practicality for large data sets. The concept meets the requirements of operational business intelligence and provides insights for the design of future data warehouse architectures.