Predicting Driver Behavior with Big Data Analytics by Marshall Presser and Bjorn Boe
Video from DevIgnition 2014 - Elephant Talk! See devignition.com for details.
Managing risk is at the heart of the insurance industry. In this talk, we'll solve the problem of assessing driver behavior with a case study using Telematic data processed with Python, Java, Map/Reduce, SQL on Hadoop (HAWQ), Redis, and Cloud Foundry to assist an insurance company in mapping trips by their policy holders and using that data to predict driver behavior. The audience should have a basic understanding of Hadoop
Marshall Presser is Federal Field CTO for Pivotal, a company building Platform as a Service for doing Big Data Analytics, deriving insights from the data, and providing a platform for productizing those insights for end users. Prior to coming to Pivotal, he worked in parallel computing for scientific and business applications as well as a stint in compiler and OS development.
Bjorn Boe works as a Field Engineer at Pivotal, working with customers to solve challenges related to cloud, big data and Internet of Things. He has a background in software development and architecture, distributed systems and databases.