Graph technology has become a requirement for the modern enterprise. Companies in virtually every industry, from healthcare to energy to financial services, are applying the power of graph analytics ...

Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring. These methods ...

Whether you’re genuinely interested in getting insights and solving problems using data, or just attracted by what has been called “the most promising career” by LinkedIn and the “best job in America” ...

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

These past few months have not been kind to any of us. The ripples caused by the COVID-19 crisis are felt far and wide, and the world's economies have taken a staggering blow. As with most things in ...

The problem: The app must store a collection of people and who they know. Sometimes it must find out everyone who knows someone who knows Bob. Sometimes it must look further for everyone who is three ...

Debate and discussion around data management, analytics, BI and information governance. This is a guest blogpost by Jim Webber, Chief Scientist at graph database provider Neo4j. It discusses Knowledge ...

The way you present your Excel data can make a significant impact on how your message is received. Excel, a tool that most professionals are familiar with, has immense potential for creating visually ...

A semantic graph database technology vendor is supporting a key specification designed to validate graph-based data against a set of conditions that specify the “shape” of data. The goal is a more ...