Graph analytics improves AI decision-making by uncovering hidden patterns and relationships in complex data, delivering more accurate insights with richer context than traditional analytics. Yet ...

As the sources, types, and amounts of data continue to expand, so will the need for different kinds of analytics to make something of that data. Unfortunately, there is not a one-size-fits-all ...

How would you feel if you saw demand for your favorite topic — which also happens to be your line of business — grow 1,000% in just two years’ time? Vindicated, overjoyed, and a bit overstretched in ...

If your team struggles to view how information is consumed from a digital asset management (DAM) system, consider the option of a graph database. Graph databases are among most promising new analytic ...

Part I of our series on graph analytics introduced us to graph analytics, and its brethren graph databases. We talked about the use of graph analytics to understand and visualize relationships between ...

LONDON--(BUSINESS WIRE)--Graph technology and graph analytics are used across industries for different purposes, including social media analysis, risk analysis, fraud detection and prevention, and ...

Even though graph analytics has not disappeared, especially in the select areas where this is the only efficient way to handle large-scale pattern matching and analysis, the attention has been largely ...

The latest trends and issues around the use of open source software in the enterprise. As defined nicely here by Hitachi Vantara’s Bill Schmarzo, “Graph analytics leverage graph structures to ...

When the world’s largest healthcare company by revenue went looking for a technology solution that could improve quality of care while reducing costs, the search took ten years. What they found—an ...

Graph databases offer a more efficient way to model relationships and networks than relational (SQL) databases or other kinds of NoSQL databases (document, wide column, and so on). Lately many ...