Volvo utilized data mining in an effort to discover the unknown valuable relationships in the data collected and to assist in making early predictive information. It created a network of sensors and CPUs that were embedded throughout the cars and from which data was captured. Data was also captured from customer relationship systems (CRM), dealership systems, product development and design systems and from the production floors in their factories. The terabytes of data collected was streamed via the cloud to its centralized hub or Volvo Data Warehouse. From the warehouse Volvo received real-time analysis of data captured. The data could then be archived and accessed on demand.
How Volvo Car Corporation Transforms Data into Knowledge
From the Volvo Data Warehouse all the data from the various data streams is analyzed and transformed into knowledge. The information generated gives Volvo the ability to early predict potential issues such a mechanical problems which would show up only after the manufacturing process is completed. The data is insightful and Volvo can fix a problem during the manufacturing process before it becomes a hazard to customers. This real time analysis gives Volvo a competitive edge. Better maintenance plans for the vehicles are designed because they can predict when parts for various cars need to be checked or replaced. Volvo became the first company to implement an Early Warning Engine leveraging analytics. This delivers failure predictions for every diagnostic trouble code, component, and system and vehicle variation in the motor vehicle industry. Volvo is able to prioritize and focus on issue resolution. Setting priorities on future failures enables Volvo to be efficient in acting on emerging issues with a data-driven approach. Volvo is enabled to provide better service to its customers and maintain its reputation of leading the automotive industry in
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