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.

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 relationships ...

Graph database maker Neo4j Inc. today introduced a version of its Aura managed service aimed at data scientists.The new offering complements an existing managed version of its core graph database ...

Katie Roberts, PhD, data science solution architect at Neo4j, joined DBTA's webinar, 'Solving Data Challenges with Knowledge Graphs and Context-Aware Recommendation Systems,' to explore how building ...

Neo4j Graph Data Science makes it easy for data scientists to work within their existing data pipeline of tools across their ecosystem. Data scientists can use Neo4j Graph Data Science on-premises, ...

TigerGraph, a company that provides a graph database and analytics software, has expanded its data science library with 20 new algorithms, bringing its total to more than 50 algorithms.. Graph ...

Gartner Inc. has forecast that graph technologies will be used in 80% of data and analytics use cases, up from 10% in 2021. SQL support A key feature of the partnership is the use of SQL to build ...

Data science and machine learning features: Notebooks and Graph Neural Networks GQL still has some way to go. Standardization efforts are always complicated , and adoption is not guaranteed across ...