The Emergence of the Enterprise DataFabric

Editor’s Note: This presentation was given by Mark Kvamme and Clark Richey at GraphConnect San Francisco in October 2016. Presentation Summary Enterprises are faced with a variety of challenges when it comes to managing data, largely due to the disparate… Learn More →

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How NASA Finds Critical Data through a Knowledge Graph

Editor’s Note: This presentation was given by David Meza at GraphConnect San Francisco in October 2016. Here’s a quick review of what he covered: What is a knowledge architecture? What are the benefits of a knowledge architecture? The power of… Learn More →

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Fraud Prevention with Neo4j: A 5-Minute Overview

Fraud is becoming increasingly difficult to discover and prevent as fraudsters are increasingly employing complex techniques and advanced technologies to perpetrate fraud. Who Are Today’s Fraudsters? Today, fraudsters are organized in groups, possess synthetic or manufactured identities – which in… Learn More →

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The Top 10 Can’t-Miss Speakers at GraphConnect Europe [2017 Edition]

You already know the top nine reasons you should attend GraphConnect Europe this year, but besides the fantastic networking opportunities with some of the world’s most advanced graph database developers, architects and CTOs, there’s one reason that outshines them all:… Learn More →

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This Week in Neo4j – 8 April 2017

Welcome to this week in Neo4j, where we round up what’s been happening in the world of graph database in the last seven days. This week we look at how to create a Twitter clone using Neo4j, the Neo4j data… Learn More →

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The 5-Minute Interview: Antonio Molins, VP of Data Science at Miroculus

“We think it’s good to use the right tool for the right problem — and graph databases are the right tool if you are focusing on relationships,” said Antonio Molins, Vice President of Data Science at Miroculus. Choosing the right… Learn More →

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Building a Real-Time Recommendation Engine with Data Science

Editor’s Note: This presentation was given by Nicole White at GraphConnect Europe in April 2016. Here’s a quick review of what she covered: Basic graph-powered recommendations Social recommendations Similarity recommendations Cluster recommendations – What we’re going to be talking about… Learn More →

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Navigating the Complexity of Heart Failure Research with Neo4j [Community Post]

[As community content, this post reflects the views and opinions of the particular author and does not necessarily reflect the official stance of Neo4j.] Life sciences deal with complex, dynamic systems composed of interconnected elements driving health and disease (e.g.… Learn More →

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The Secret to More Efficient Data Science with Neo4j and R [OSCON Preview]

It’s a sad but true fact: Most data scientists spend 50-80% of their time cleaning and munging data and only a fraction of their time actually building predictive models. This is most often true in a traditional stack, where most… Learn More →

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