Mark Needham is a Support Engineer for Neo4j. He also blogs about software development at markhneedham.com.
Amy is the Analytics and AI Program Manager at Neo4j. She believes a thriving graph ecosystem is essential to catalyze new types of insights. Accordingly, she helps ensure Neo4j partners are successful. In her career, Amy has consistently helped teams break into new markets at startups and large companies including EDS, Microsoft, and Hewlett-Packard (HP). She most recently comes from Cray Inc., where she was the analytics and artificial intelligence market manager.Amy has a love for science and art with an extreme fascination for complexity science and graph theory. When the weather is good, you’re likely to find her cycling the passes in beautiful Eastern Washington.
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
Today’s most pressing data challenges center around connections, not just tabulating discrete data. Graph analytics accelerate breakthroughs across industries with more intelligent solutions. This blog series is designed to help you better leverage graph analytics so you can effectively... read more
According to Gartner’s 2018 Magic Quadrant for Data Management Solutions, the biggest reason for using the Neo4j graph database "is to drive innovation.” This blog series is designed to help organizations better leverage graph analytics to effectively innovate and develop intelligent... read more
According to Gartner, "graph analysis is possibly the single most effective competitive differentiator for organizations pursuing data-driven operations and decisions.” Why did Gartner say this? Because graphs are the best structure for today's complex and ever changing data, and if you can... read more
Until recently, adopting graph analytics required significant expertise and determination, since tools and integrations were difficult and few knew how to apply graph algorithms to their quandaries and business challenges. It is our goal to help change this. We are writing this blog series to... read more
