Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

But following today’s announcement of a $325-million funding round that values the graph database company at over $2 billion, Neo4j expects to see more widespread use of graph algorithms for data ...

Graph data science is an emerging field with a lot of promise, but it’s being hamstrung by the need for practitioners to have lots of data engineering and ETL skills. Now Neo4j is hoping to drive that ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

Neo4j for Graph Data Science will help us to identify where we need to direct biomedical research, resources, and efforts." Neo4j continues to be something of a harbinger of the growing need for ...

Data science is “a growing segment of our enterprise customers that made up about 30% of new customers last quarter,” said Alicia Frame, senior director of graph data science at Neo4j.

For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of ...

But Neptune also exemplifies another important development in graph databases: integration of data science and machine learning features.