Complex images such as graphs and charts make it easy to represent trends and complex data relationships to visual users. Other complex images can include diagrams and illustrations that require a ...

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 ...

Data visualization is the graphical representation of information and data via visual elements like charts, graphs, and maps. It allows decision-makers to understand and communicate complex ideas to ...

Graph machine learning (or graph model), represented by graph neural networks, employs machine learning (especially deep learning) to graph data and is an important research direction in the ...

Identity management for cybersecurity is inherently a complex graph problem due to the vast, dynamic, and interconnected nature of modern IT environments. The Fast Company Executive Board is a private ...

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 ...

Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Jul 03, 2025, 10:43am EDT Business 3d tablet virtual growth ...

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” ...

Debate and discussion around data management, analytics, BI and information governance. This is a guest blogpost by Amy Holder from Neo4j. She examines recent interest in graph databases as the basis ...