Neo4j Enables up to 100x Faster Analytics and Real-Time Decision-Making

Discover Neo4j’s new capabilities and features, including parallel runtime, native CDC, knowledge graph embeddings, and new algorithms.

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Supply Chain Intelligence: Future-Proof Your Supply Network

How can supply chain managers anticipate risks, avoid disruptions, and control costs? Supply chain intelligence, powered by graph technology.

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Knowledge Graph vs. Vector Database for Grounding Your LLM

Explore the benefits of grounding Large Language Models (LLMs) in knowledge graphs vs. vector databases for reliable and accurate data.

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Predictive Modeling Techniques: Types, Benefits & Algorithms

Predictive modeling helps businesses improve workflows, operations, and their bottom line. Learn the benefits, challenges, and common tasks and algorithms.

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Top Speakers to Watch Out for at GraphSummit Europe 2023

Top speakers to watch out for at GraphSummit Europe 2023! Learn from graph experts in leading organizations at your nearest GraphSummit city.

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Graphs4APAC: Enabling, Empowering & Engaging Professionals in APAC

Graphs4APAC empowers next-generation graph professionals in APAC to learn, get certifications, and be successful with graph technology.

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Graph for Equitable Financial Opportunities: The 5-Minute Interview With Arthur Zverko

Because of how we approach data in our platform and look at it from a developer-friendly way – and thinking of the data just as JavaScript objects – the traversal of graphs seemed like a natural pick for us. That’s why we chose to go with Neo4j,” says Arthur Zverko, Software Team Lead at financial platform Equitybee.

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Unlock the Power of Graph Data Science With AuraDS Enterprise on AWS

AWS and Neo4j are offering scalable and intelligent tools to help data scientists quickly gain insights from their data. By adding graph algorithms and embeddings to ML pipelines, data scientists can now explore billions of data points in seconds, identify hidden connections, and generate compelling visualizations to make informed decisions.

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How to Explore SAP Sample Data in Neo4j – Graph for ERP Part 2

Learn how to load SAP data and analyze the relationships between these entities to gain insights and extract meaningful information.

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Graphs for Ease and Scalability in the Auto Industry: The 5-Minute Interview with Michal Stefanak

​​”I think graph database is the only database we should use – at all. It’s the best one. After using Neo4j, I don’t want to go back to relational databases. The Neo4j database is perfect. It’s exactly the way people think and how you draw all the UML diagrams and everything. It’s exactly what you do,” says Michal Stefanak, Programmer at VOLKE.

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The Power of Knowledge Graphs and Conversational AI

It’s no longer a question if Conversational AI will change the way we work, but rather how much. The explosive growth of OpenAI’s ChatGPT and now Microsoft’s AI-powered Bing and Google’s Bard show the appetite for conversational AI among consumers is insatiable.

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Announcing Neo4j Graph Data Science 2.3

We’re excited to announce Neo4j Graph Data Science 2.3, which includes new algorithms, new graph embedding, and performance improvements.

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Graph Analytics: The Future in Data Science?

Graph databases are designed to efficiently store and query connected data by using a node and relationship-based format, making them particularly equipped to solve problems when understanding those connections are critical.

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Enabling Low/No Code Engineering Experience and Operationalizing Information Models

Discover how Yokagawa drives digital transformation by building a knowledge graph that enables low-code engineering experience.

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The Visual Simplicity of Graph: The 5-Minute Interview With Folks From Fractal 5

“Everything is a graph. So as far as Neo’s development and the advances it’s made in the speed and adoption of more data – and more mature data – everyone can leverage all the developments in regards to graph neural networks and such. And that lends itself to a better world altogether,” Bjartur Hjaltason, machine learning engineer at Fractal 5.

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Standard Chartered: Threat Intelligence Using Knowledge Graphs

Learn how Standard Chartered protects their customers’ money, assets, and data from threats using knowledge graphs.

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How DBS Connect Knowledge with a Knowledge Quotient Framework

Discover how DBS brought their siloed customer data together using knowledge graphs to achieve customer 360.

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How the Australian Department of Infrastructure Applies Graph

Learn how the Australian Department of Infrastructure uses graph technology to improve the analytics of their transportation system.

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Better AI With Neo4j and Azure Machine Learning

Learn how to integrate Neo4j’s Graph Feature Engineering capabilities with Azure Machine Learning for better AI.

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Digital Twin for the Construction Industry: How Neanex Uses Neo4j

Discover how Neanex creates digital twins of real-world physical objects or processes to solve the data problem in the construction industry.

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Demystifying Environmental, Social, and Governance (ESG) Reporting With Graphs

Learn how EY uses knowledge graphs to meet the demands for environmental, social, governance (ESG) reporting.

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Are Economists Right or Wrong? Connecting Patent Data in Neo4j

Graph analytics has become a useful tool in economics to improve our understanding of patent data and the knowledge economy.

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London’s Traffic Operations Digital Twin: The 5-Minute Interview With Andy Emmonds

Andy Emmonds explains how Transport for London uses graph databases and digital twin to build a smart decision-supporting system.

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4 Best Practices for Introducing Your Teams to Graph Data Science

Ready to introduce graph data science to your teams? Here are 4 best practices to give them the confidence to solve graphy problems.

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DXC Career Navigator: Data Driven Employee Career Development and Engagement

Discover how the DXC Career Navigator uses knowledge graphs to connect siloed employee data and generates intelligent career recommendations.

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