For years, the amount of data generated in many industrial production plants has been said to have great potential for improving maintenance processes. In order to leverage this potential in practice, however, it is necessary to overcome a number of hurdles from automated data exchange, linking separate data sources, evaluating the actual data quality to the automated evaluation of existing data. In the project “Smart Maintenance” together with our industrial partners BMW Motors Steyr and BRP Rotax, we have developed a practical procedure to analyze the operating-, error- and sensor-data in a user-friendly web interface. This enables us to make the data utilizable for improving maintenance processes. The core functionality consists of various filter and aggregation mechanisms. Based on these different forms of visualization allow the intuitive interpretation of events in order to integrate new contexts into the daily routine of maintenance planning.