Are you wondering how you can get started with graph data science (GDS)? In this blog post, we're going to give you 10 project tips and some resources to guide you from the beginning of your graph data science project to its production. As opposed to technical details, here we’ll help you... read more
Editor’s Note: This presentation was given by Mark Needham and Amy Hodler at NODES 2019 in October 2019. Presentation Summary Our names are Mark Needham and Amy Hodler. Mark works on the Neo4j Labs team, which is a team that helps Neo4j integrate with different technologies and explores... read more
Today, graph data science (GDS) is usually applied in business with one or more major aims in mind: better decisions, increased quality of predictions, and creating new ways to innovate and learn. These goals are increasingly tied to tangible benefits, such as reduced financial loss, faster... read more
Graph approaches to data are exploding. In the commercial world, graph-based analysis is used to explore deeper meaning in data you already have, improve forecasts and make better predictions. This accelerating use in business is due to the increasing connectedness of data, breakthroughs... read more
We’re happy to share recent improvements to the Neo4j Graph Algorithms library. These updates include optimizations at several layers, improved configuration and usability, as well as specific feature requests. A big "thank you" to those who provided suggestions on how to better serve... read more
Graph enhancements to artificial intelligence (AI) and machine learning (ML) are changing the landscape of intelligent applications. For more videos like this one, check out upcoming and on-demand video content in the Neo4j Webinar library. In this session, we focus on how using... read more
Today is the first-ever Global Graph Celebration Day! Graph enthusiasts all over the globe are honoring the birthday of Leonhard Euler, the inventor of graph theory, with 60+ events worldwide. As part of today's graph-inspired festivities commemorating Euler, we have an exciting announcement to... read more
Graph analytics have value only if you have the skills to use them and if they can quickly deliver the insights you need. This blog provides a hands-on example using Neo4j on data from Yelp’s Annual Dataset challenge. Graph algorithms are easy to use, fast to execute and produce powerful... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you better... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you... read more
Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series is designed to help you... read more
The Neo4j Graph Algorithms Library is used on your connected data to gain new insights more easily within Neo4j. These graph algorithms improve results from your graph data, for example by focusing on particular communities or favoring popular entities. This blog series is designed to help you... read more
According to Frost & Sullivan, “Graphs are one of the unifying themes of computer science – an abstract representation that describes the organization of transportation systems, human interactions and telecommunication networks. That so many different structures can be modeled using a single... read more
At a fundamental level, a native graph platform is required to make it easy to express relationships across many types of data elements. To succeed with connected data applications, you need to traverse these connections at speed, regardless of how many hops your query takes. This blog series... read more
Graph technologies are the scaffolding for building intelligent applications, enabling more accurate predictions and faster decisions. In fact, graphs are underpinning a wide variety of artificial intelligence (AI) use cases. This blog series is designed to help you better leverage graph... read more