But of course, exploring a beergraph is not really a "business-y" use case. So I decided I would record a Bloom demo using a realistic dataset that centers around using Neo4j for Fraud Detection purposes. You will find all of the important concepts of the Beergraph demos here as well:
- navigating the graph using graph patterns
- using nifty selection / deselection techniques to only show what you need in the graph
- creating better visualizations with colours and icons
- editing the graph straight from the Bloom interface
- creating custom search phrases for business uses and giving them near-natural language graph search capabilities.
I hope this is useful for you - and as always, comments would be more than welcome.