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.

Graph theory isn’t enough. The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them) — has been an invaluable way ...

Regardless of what data model (s) you choose to bring into your company’s data strategy, it’s important to have the right people and processes in place to make these models work.

Publication title Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests Purdue author Faming Liang Authors Bochao Jia, Faming Liang Publisher Chapman & Hall ...

Graph analytics databases have been described as embodying the next generation of data storage connected with AI, and that's what innovation is all about: a new-and-improved version of how ...

Traditional hydrological models are increasingly being replaced or enhanced by data-driven approaches capable of learning ...

The graph database landscape has been fragmented, with property graphs & RDF representing different ways to model, store, and query data, with no standard way of interoperability.

According to Gartner’s Top 10 Data and Analytics Trends for 2021, knowledge graphs are the foundation of modern data and analytics, with capabilities to enhance and improve user collaboration ...