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.

Enterprises that want to use powerful graph algorithms to discover relationships hidden in their data now have an easier path to get there thanks to the new data science library unveiled today by ...

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 ...

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.

Neo4j, a leading graph data platform, is unveiling Neo4j Graph Data Science, the company's comprehensive graph analytics workspace built for data scientists. The platform is now available with new and ...

Neo4j for Graph Data Science was conceived for this purpose – to improve the predictive accuracy of machine learning, or answer previously unanswerable analytics questions, using the ...

Neo4j, a provider of graph technology, is launching Neo4j for Graph Data Science, a data science environment built to harness the predictive power of relationships for enterprise deployments. Neo4j ...

Graph database and analytics software company TigerGraph has expanded its data science library to more than 50 algorithms.

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

Alexander Christensen's recent study probably won't rewrite 40 years of history in the field of psychology, but he hopes that ...