In various industry sectors all over the world, the ongoing digital transformation helps to unlock benefits for individual components, involved processes, stakeholders as well as the overarching system (e.g., the national economy). In this context, the rail transport sector can particularly benefit from the increased prevalence of sensor systems and the thereby increased availability of related data. As rail transport, by nature, is an integrated transport mode that contains both freight and passenger transport within the same transport network, benefits achieved for the service quality of freight transport also lead to improvements for passenger transport (e.g., punctuality or uptime of rolling stock). This technical paper presents a method to monitor the condition of the existing rail infrastructure as well as the rolling stock by obtaining insights from raw sensor data (e.g., locations and acceleration data). The data is collected with telemetry-units (i.e. multiple sensors integrated with a telematics device to enable data transmission) mounted on a fleet of on-rail freight wagons. In addition, the proposed method is applied to an exemplary set of extracted real-world data.