Data Science and Neo4j

Presenter - Kenny Darrell, Senior Data Scientist, Elder Research, Inc

Abstract - In a typical project data scientists often find themselves at odds with conventional RDBMS technologies. Often flat files will be used until enough knowledge is gathered to build a schema, usually around the time exploration and modeling are coming to an end. This can be painful. Graph Databases - Neo4j especially - can provide a powerful data storage mechanism that alleviates some of these headaches. In order to utilize this machinery though, bindings are needed in the tools data scientists are already using. The RNeo4j package can foot the bill, allowing you to store and query data in Neo4j and perform any of the vast number of statistical and graphing operations in R.