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.

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.

Data meets science: Open access, code, datasets, and knowledge graphs for machine learning research and beyond Written by George Anadiotis, Contributor Feb. 16, 2021 at 7:11 a.m. PT Science and ...

Debate and discussion around data management, analytics, BI and information governance. This is a guest blogpost by Jim Webber, Chief Scientist at graph database provider Neo4j. It discusses ...

Ever since the introduction of the Google Knowledge Graph, a growing number of organizations have adopted this powerful technology to drive efficiency and effectiveness in their data management ...

According to Gartner’s Top 10 Data and Analytics Trends for 2021, knowledge graphs are the foundation of modern data and analytics, with capabilities to enhance and improve user collaboration ...

Katie Roberts, PhD, data science solution architect at Neo4j, joined DBTA's webinar, 'Solving Data Challenges with Knowledge Graphs and Context-Aware Recommendation Systems,' to explore how building ...

Graph data science is an emerging field with a lot of promise, but it’s being hamstrung by the need for practitioners to have lots of data engineering and ETL skills. Now Neo4j is hoping to drive that ...

Auer is a Data Science professor with many contributions in Knowledge Graph research and is leading ORKG. Dr. Auer identified two key issues in scientific research.

As the head of multiple data engineering and data science teams over the years, he has developed more than his share of them to enable his teams to query data on large amounts of real-time data. “They ...