Introduction While glancing into the future of automotive and identifying the potential opportunities, challenges, success, and failure the industry should encounter while shifting toward electrification, electric vehicle (EV) telematics will continue to be a vital process. The rise in data dependency within automotive is a widely acknowledged notion, but it is still so critical that it is worth reemphasizing again—especially as the industry navigates through the early stages of a new, electrified era. Sophisticated vehicles can achieve and maintain efficient operability while adhering to safety performance standards because of the telematics and analytics involved in the product development process. The importance of pulling information through telematics will grow in parallel to the complexity of EV development both now and in the future because telematics may become more complex as more data is accessed and utilized. The EV market is becoming a driving force regarding where the industry is shifting toward, meaning that telematics, along with a meticulous analytics plan, will add valuable context to the information collected in products’ software and integrated technology systems. To maintain the development of safety-optimized vehicles with advanced technology,  telematics is a needed asset.

How to Build Master Data Systems: Architecture, Trade-offs, and Constraints   Introduction Master data has a critical role to play when guaranteeing organizational visibility, operational efficiency, and product functional safety. As data becomes more complex in the future, the need for master data in automotive will continue to increase. This blog is the second of a 3-part series focused on the importance of master data, the technical architecture of master data systems, and the trade-offs and constraints that come with building these systems, ultimately proposing what a proper master data plan looks like, which can help organizations achieve growth and success. The content in each blog is centralized around the main topics from LHP’s DAS Master Data webinar panel that we held this past June: