An automobile insurance firm offers a discount to drivers who allow the insurance to collect telematics data. In order to score each driver and to create a model of all customer driving patterns, Ultra Tendency architected a system by which the data ingest takes place from AWS with Kafka for messaging and Spark for real-time evaluation of any given drive, based on rules concerning how well or poorly someone drove. When that score is calculated, it is stored on HBase, from which it will be made available to a mobile app, operated on Kubernetes. Customer’s data scientists then deploy the Cloudera Data Science Workbench to create and improve driver models. 

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