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In this talk we’ll explore powerful analytic techniques for graph data. Firstly we’ll discover some of the innate properties of (social) graphs from fields like anthropology and sociology. By understanding the forces and tensions within the graph structure and applying some graph theory, we’ll be able to predict how the graph will evolve over time. To test just how powerful and accurate graph theory is, we’ll also be able to (retrospectively) predict World War 1 based on a social graph and a few simple mechanical rules.Then we’ll see how graph matching can be used to extract online business intelligence (for powerful retail recommendations). In turn we’ll apply these powerful techniques to modelling domains in Neo4j (a graph database) and show how Neo4j can be used to drive business intelligence. Don’t worry, there won’t be much maths.
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Dr. Jim Webber is Chief Scientist with Neo Technology, the company behind the popular open source graph database Neo4j, where he works on R&D for highly scalable graph databases and writes open source software. His proven passion for microservices ecosystems and REST translate into highly engaging workshops that foster collaboration and discussion.