A growing trend in the auto insurance business is the use of telematics in which a driver’s behavior is monitored directly and the information is transmitted to an insurance company. The company assesses the risk the driver poses and charges premiums accordingly. This massive collection of raw telematics data can be stored in Hadoop. An analyst can use the Aster Database to perform a path analysis on the telematics data to determine which driving behaviors are most likely to lead to an accident, such as frequent hard breaking followed by sudden lane changes. Once identified, those patterns can be loaded into the Teradata Database for analysis. The analyst can then write a query to the Teradata Database that moves a filtered set of telematics data from Hadoop into the data warehouse for analysis against the patterns to identify drivers with the highest risk. The risk information is cross-referenced with customer data in the warehouse to determine whether a driver is a high- or low-value customer, and the analyst can then make recommendations on insurance premium adjustments.