Featured Post

This Week in Neo4j: NFTs, Extension for Liquibase, Visualizations in Jupyter, CSV Mapping Editor, and More

This week's featured piece is about the CSV mapping editor, one of Kineviz GraphXR's most powerful tools that is especially handy if you're just getting started with Neo4j. In the video, you'll see a workflow that takes CSV data into GraphXR and writes it to a Neo4j database. Set up and start a... read more


The Customer Journey Is a Graph

Editor's note: This presentation was given by Matt Butler at GraphConnect 2022. Bonsai Data Solutions and Cambridge Intelligence have worked together to help clients understand their customer journey. Bonsai is a business intelligence and data advisory company, and we’ve partnered with... read more


This Week in Neo4j: GraphQL, GraphXR, Marvel Studios API, Speech to Cypher, Free Training, and More

"Full Stack GraphQL Applications," a book by William Lyon, is hot off the presses in both print and ebook formats from Manning Publications. This book shows you how to develop full stack GraphQL applications using GraphQL, React, Apollo, and Neo4j database as well as how to deploy our... read more


Using Graphs to Unlock Forensics: The 5-Minute Interview With Thomas Larsen

“What makes me excited about graphs is I don't know where this can take us. I see a lot of possibilities. In fact, it's a bit overwhelming knowing where we can go with it,” says Thomas Larsen, Senior Manager of Forensics Analytics at ABB. We’ve got another 5-Minute Interview for... read more


Design Thinking for Graph Data: The Secret to Successful Graph-Powered Apps

Design thinking is the secret to successful graph-powered apps. My organization, Predictive UX, designs graph-based applications. We come at it from a human-first user experience perspective and work primarily with enterprise organizations on complex content and data projects. I want to share... read more


Niklas Saers

This Week in Neo4j: CSV Import, Rails Integration, Better Farming, ML for Graphs, and More

In this week's newsletter, researchers at UCLA DataResolutions set out to train a model to predict team assignments of their members based on who they know in the organization. The project integrates a graph deep learning pipeline with a knowledge graph to create a complete stack of network... read more