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This Week in Neo4j – COVID-19 Contact Tracing, De-duplicating the BBC goodfood Graph, Stored Procedures in Neo4j 4.0, SARS-CoV-2 Taxonomy

Hi graph gang, In this week’s video, Lju shows how to de-duplicate ingredients in the BBC goodfood dataset. Rik Van Bruggen starts a COVID-19 Contact Tracing Graph blog series, I build a SARS-Cov-2 taxonomy graph, and Martin Preusse tells us all about the Covid Graph Knowledge... read more


Catch this week's GraphCast: Getting Started with Arrows

#GraphCast: Getting Started with Arrows

Welcome to this week's #GraphCast – our series featuring what you might have missed in Neo4j media from the past fortnight. Last time, our Editor-in-Chief, Bryce Merkl Sasaki, broke down unlimited scalability with Neo4j 4.0, including vertical and horizontal scalability as well as database... read more


How the Professional Services Team at Neo4j built an enterprise knowledge graph.

Discovering Hidden Skills with an Enterprise Knowledge Graph

Within a growing organization, finding the right information can take up a good part of your day. As teams and people become more spread out, both geographically and organizationally, knowledge becomes exponentially harder to find. In addition, when you’re busy, doing work often gets... read more


Learn about Spring Data Neo4j RX.

Spring Data Neo4j RX 1.0 Is Now Available

Over the last year, we developed a new version of Spring Data Neo4j here at Neo4j, and we are proud to announce its general availability: Spring Data Neo4j RX 1.0 (or short SDN/RX). Spring All the Way Spring Data Neo4j RX is not dependent on any Object Graph Mapper library, but brings all... read more


Learn about graph-related projects for COVID-19 and how to get involved.

Graphs and the Strategic Response Efforts to COVID-19

A pandemic proliferates through a network of connections. Fighting against a spreading pandemic is a massive, comprehensive issue that affects health, supply chain and food systems, as well as many other economic structures. Graphs are perfectly suited for handling connected data, from... read more


Financial Fraud Detection with Graph Data Science: Analytics and Feature Engineering

Financial fraud is growing and it is a costly problem, estimated at 6% of the Global Domestic Product, more than $5 trillion in 2019. Despite using increasingly sophisticated fraud detection tools – often tapping into AI and machine learning – businesses lose more and more money to... read more