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

So, knowledge graphs are in the Hype cycle for emerging technologies now. Not bad for a technology with more than 20 years of history. ... NBA analytics and RDF graphs: Game, data, ...

Graph data stores can efficiently model, ... This is why Gartner has included knowledge graphs in its 2020 hype cycle for AI, at the peak of inflated expectations, no less.

In recent years, knowledge graphs have become an important tool for organizing and accessing large volumes of enterprise data in diverse industries — from healthcare to industrial, to banking ...

How do I find what I want to find?’ whether I’m using all that data to drive some AI or machine learning processes or whether I’m using it for reporting or whatever.” It’s a “virtuous cycle” between ...

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.

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.

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.