Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around ...

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.

The world of financial markets can shift in moments, and newcomers often find themselves drowning in a sea of numbers, charts ...

As graph database adoption accelerates, new data infrastructures will emerge to eliminate many of the scale struggles of graph database models. Written by eWEEK content and product recommendations ...

As Neo4j explains, graph analytics can improve AI decision-making by “uncovering hidden patterns and relationships in complex data, delivering more accurate insights with richer context than ...

How graph databases can be used to explore and analyse the decentralised XRP ledger, focusing on exploring networks of fraudulent accounts and distribution patterns.

Finding patterns in data on a graph or chart is known as ‘interpreting relationships’.Plotting a chart or graph helps to show a pattern in the data - how the dependent variable depends on the ...

A June Gartner report, AI Design Patterns for Knowledge Graphs and Generative AI, underscores this notion, emphasizing that knowledge graphs offer an ideal partner to an LLM, where high levels of ...

Benchmark data show near linear scalability when querying three terabytes of cyber data with 20 billion graph edges and 212 billion edge properties. The combination of the graph search tool and an SMP ...

Thanks to their visual simplicity, bar graphs are popular tools for representing data. But do we really understand how to read them? New research from Wellesley College published in the Journal of ...