What is it?
Neo4j Graph Data Science
Neo4j Graph Data Science is a connected data analytics and machine learning platform that helps you understand the connections in big data to answer critical questions and improve predictions.
HOW DOES IT WORK?
Unlock Insights Trapped in Rows and Columns
Access 65+ pretuned graph algorithms and machine learning (ML) modeling to analyze your connected data. Conveniently available in a single workspace, the analytics surface and graph database are fully integrated.
Try the Graph Data Science Sandbox
WHY DATA SCIENTISTS PREFER NEO4J
A Data Science Workspace
That Works for You
Neo4j Graph Data Science is the only connected data analysis platform that unifies the ML surface and graph database into a single workspace.
This way, data scientists run algorithms and ML models without jumping between tools for ETL.
Learn what’s new in Graph Data Science
Easy to Use
- Load data into a graph from any source
- Integrate with your data pipeline tools
- Fund your investment with committed spend on Google Cloud Platform, Amazon Web Services, and Microsoft Azure marketplaces
Start with free courses
Use In-Graph ML
- Native Python API client
- Access to over 65 pretuned graph algorithms
- A single API for data load, analysis, and write-back
View Neo4j graph algorithms
- Scale to hundreds of billions of nodes and relationships
- Includes a single, unified model training and deployment environment
- Offers automated MLOps
Learn how Meredith scales
ADVANTAGES OF GRAPH-NATIVE MACHINE LEARNING
Why Neo4j Graph Data Science?
In a graph, your data shows you what’s important,
what’s unusual, and what’s coming next.
Answer business critical questions and make predictions
Rather than looking at row or column headers, graphs focus on data relationships. Graphs are a more natural, connected way to look at and analyze data for deeper context and unearthing hidden patterns and insights.
Accelerate your path from proof of concept to production
Access a single interface that includes both your ML surface and graph database. Easily integrate with your favorite data science tools and scale your analysis across hundreds of billions of nodes and relationships.
Understand relationships and improve your models
A native Python client, library of 65+ pre-tuned graph algorithms, connected data prep techniques, data connectors, and graph-native ML give data scientists everything they need without having to switch between interfaces.
DESIGNED FOR DATA SCIENTISTS BY DATA SCIENTISTS
Simplify Your Data Science Workflow
Get what you need to go from proof of concept to production quickly, with a wide selection of deployment options, user tools, and data connectors that make it easy to add graph data science to your existing data pipeline.
Fully Hosted Graph Data Science
Simplify deployment and management of graph data science with a fully managed, pay-as-you-go option, AuraDS.
Query and Test
Write queries and explore the contents of your Neo4j graph database using an intuitive development environment.
Explore, investigate, and present Neo4j graph data with our no-code graph data visualization solution, Bloom.
Use a single API for data load, analysis, and write-back. A Python client and Neo4j connectors are available.
GRAPH DATA SCIENCE USE CASES
Discover How Data
Scientists Use Neo4j
Graph data science helps organizations answer some of their most difficult and complex questions by moving the data out of the silos of rows and columns and into an easy to analyze graph.View all use cases
Detect and Identify Fraudsters
Analyze relationships and behaviors to detect fraud across banking, insurance, and government programs.
Increase Customer Satisfaction
Create stronger recommendation engines to help increase conversion rates, reduce churn, and increase average cart size.
Improve Route Optimization
Manage supply chain inefficiencies by calculating what-if scenarios and predict future issues with pathfinding algorithms.
Resolve Entities and Identities
Unify entities for marketing, payments, usage, and more to provide the best customer view possible.
“The most surprising result was really seeing how connected the data was. I used to think that we knew this data really well when we looked at it individually from each different data stream, but when you combine them all together and you actually look at the datasets as a whole, it makes you realize that it’s like trying to solve a Rubik’s Cube by only looking at one side.”
Benjamin Squire, Senior Data Scientist, Meredith
“We wanted a partner that would provide the type of scale we needed on graph – again, millions of nodes and edges – but also provide us with the spatial data support. And the third component is that since we are innovating, we wanted to work with somebody who would join our innovation process. We had to, together, add and configure Neo4j so that it would actually deliver what we needed.”
Ali Riaz, CEO, OrbitMI
"Neo4j Graph Data Science is a great tool because we can tweak our models over time to improve them. We have everything we need all in one place with Graph Data Science - it makes it easy for us to focus on building our business because the software works easily with our existing toolset and data science approaches."
Daniel Brady, CEO, Orita
SUPPORT & COMMUNITY
Enhance Your Graph Data
We provide expert technical support and connect you with a vibrant community to help make your experience the best it can be.