Graph Data Science features are now available in Bloom 2.3! Just select the Graph Data Science icon and choose from the available algorithms. The GDS plugin needs to be installed on the database for self-managed users, or you can use AuraDS.
To get an idea of what Bloom and Graph Data Science are capable of, read Zach Blumenfeld ’s blog on using graph technology on a freight forwarding logistics network. In this first blog in the series, he gets us started with experimentation and visualization of supply chain data using Neo4j Graph Data Science and Bloom. In his own words: “The data is obscure and unwieldy to deal with in its raw form. It is also heavily anonymized with dates and locations retracted. However, once we get it into Neo4j, you will see that, despite all this, the data almost instantaneously starts to tell a story as insights reveal themselves naturally through the network structure and things become transparent.”
Thank you, Zach!
Yolande Poirier
P.S.: You are invited to attend local GraphSummits in EMEA and APAC. To get a better understanding of what you can expect to achieve at one of these events, read Eva Delier’s blog. After the one-day events, some of the cities – such as Paris, Milan, Berlin, London, Amsterdam, and Tel Aviv – are hosting evening meetups. This is your chance to get together! Find a local event here.
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