As data complexity continues to grow and the demand for real-time insights increases, the move away from traditional relational databases and towards the adoption of graph databases will become vital.

Introducing the Segment Data Graph: A Core Innovation. ... and pass this data to the downstream tools of their choice to be used for advanced analytics, adtech, and marketing automation.

Graph databases, like Neo4j, excel in managing data that’s all about connections. They store information as entities and the links between them, making it easier to see how everything is related.

Semantic data and markup, in turn, help to connect concepts and ideas, making it easier to turn them into structured data to populate Google’s Knowledge Graph.

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 ...

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 on US abortion rate during different presidents based on real data, ... federal lawmakers have had trouble passing abortion restriction laws.