Graph analytics is a set of analytic techniques that shows how entities such as people, places and things are related to each other. Unlike traditional data analytics, which is slow and unable to ...

Available starting today, Neo4j Aura Graph Analytics is said to work with any kind of data source, including Oracle, Microsoft SQL, Databricks, Google BigQuery, Snowflake and Microsoft OneLake.

The Bulgarian graph database startup Graphwise today announced a major upgrade to its flagship GraphDB tool, adding new features aimed at boosting enterprise knowledge management and creating a more ...

Smarter AI agents need smarter data. Knowledge graphs can help by providing a shared data foundation that enables agents to ...

Graph analytics provide another arrow in our quiver – another tool that we can use against these vast amounts of social media and sensor-based data to uncover new insights about the ...

Knowledge graphs: The link between data and meaning While Google popularized the term “knowledge graph” in 2012, the concept of representing knowledge as interconnected information has roots ...

Visualizations can help you understand data better – but they can also confuse or mislead. Here, some tips on what to watch out for. 3 questions to ask yourself next time you see a graph, chart ...

Knowledge graphs should be a data executive’s secret weapon. It’s time for you to get as smart as Amazon, Facebook, Goldman Sachs, Google and other data-driven leaders.

The semantic technologies underpinning RDF knowledge graphs are primed for data mesh and data fabric architectures — and their synthesis. They’re certainly ideal for crafting data products.

“You have predictive analytics, you have prescriptive analytics, you have graph analytics, you have planning, you have rule-based reasoning,” Aref tells The Next Platform.. “The idea here is – ...