This talk will present how a small start-up (Waveonics) with no prior graphical database experience employed the simplicity, versatility and flexibility of Neo4j to handle the complex and dynamic roadway conditions found in crowdsourced street map data. We map the route taken to transit from a relational to graphical data model in support of the next generation roadside service applications for an established leader in the roadside service industry (Agero). We will show how Waveonics and Agero used Neo4j to detect and understand changing roadway conditions in order to identify emerging trends and thereby improve driver safety and the driving experience.
Recent advances in mobile device sensors, GPS location services, communication technology, crowdsourced data acquisition, affordable cloud storage, machine learning and data analytics, has opened the door to an exciting world of new services. Capitalizing on these opportunities requires providers continually organize, store, manage, access and update terabytes of information efficiently. They need databases that are powerful enough to model the complexities of the business environment and easy to modify as the environment evolves - without sacrificing the performance demanded by data analytics. Waveonics is working with Agero Mobile to explore and validate the use of graphical databases (Neo4j) to drive Agero’s mission of delivering a “holistic approach [which] helps anticipate and meet customers’ needs in a way that forms lasting connections with them.” Agero is building on Neo4j to further its leadership position in the automotive, insurance, finance and roadside service industries.
Waveonics will outline best practices used to convert 175 GB of XML relational US street map data obtained from the Open Street Map (OSM) project into a Neo4j graph database in order to successfully enable predictive roadway analytics for Agero. Attendees will learn how Neo4j’s graph data model and Cypher query language effortlessly supported an elegant representation of street map data, continually updated from customer mobile sensors, to reflect evolving road conditions.