Organizations understand the potential for turning both historical and streaming data into insights, and they have made huge investments in collecting, storing and analyzing telematics data. Unfortunately, mainstream CPU-based hardware and analytics solutions are too slow and difficult to scale. Despite large investments, far too much valuable telematics data is deleted, pre-aggregated or downsampled before analysis— most of the detail is lost. This leads to missed insights and incorrect conclusions.
Running reports infrequently and making decisions based on old telematics data is still not agile enough for use cases like: remote diagnostics for preventative maintenance; optimal infotainment advertising; and enhanced product design, informed by actual driver behavior. In this guide, you’ll learn how all players in the connected car value chain can discover more data “needles” in more data “haystacks” to build safer cars, make on-time deliveries, and precisely price usage-based insurance policies.