Solutions: Neo4j for Graph Data Science

Improve predictions using existing network structures

Today’s businesses are faced with extremely complex challenges and opportunities that require more flexible, intelligent approaches.

That’s why Neo4j created the first enterprise graph framework for data scientists – to improve predictions that drive better decisions and innovation.

Neo4j for Graph Data Science incorporates the predictive power of relationships and network structures in existing data to answer previously intractable questions and increase prediction accuracy.

Neo4j for Enterprise Graph Data Science

Neo4j Graph Data Science diagram

Combining a native graph analytics workspace and database with graph algorithms and visualization, this framework empowers data scientists to confidently operationalize analytics and machine learning models that infer behavior based on connected data.

Neo4j for Graph Data Science is comprised of the following products:

  • Neo4j Graph Data Science Library

    A toolkit with a flexible data structure for analytics and a library with five varieties of powerful graph algorithms.

  • Neo4j Graph Database

    A highly scalable, native graph database, purpose built to persist and protect relationships.

  • Neo4j Bloom

    A graph visualization and exploration tool that allows users to visualize algorithm results and find patterns using codeless search.

Graph Data Science helps businesses across industries leverage highly predictive, yet largely underutilized relationships and network structures to answer unwieldy problems.

Neo4j for Graph Data Science Industry applications

Examples include user disambiguation across multiple platforms and contacts for more personalized services and marketing, identifying early interventions for complicated patient journeys to improve outcomes, and predicting fraud through sequences of seemingly innocuous behavior.

To accomplish these goals, organizations explore the results of graph algorithms and then use predictive features for further analysis, machine learning or to support AI systems. With this approach, Neo4j customers are demonstrating that graphs bring tremendous value to advanced analytics, machine learning and AI.

Read the white paper, Artificial Intelligence & Graph Technology: Enhancing AI with Context & Connections, on how graph technology enhances machine learning and AI projects by providing context and connections within the underlying data.

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Fast Track

  • Gartner Research: COVID-19 Demands Urgent Use of Graph Data Management and Analytics

    Learn how graph data science can be used in healthcare to analyze epidemiological data, identify outbreak recurrence and flatten the COVID-19 curve.

    Get the Gartner report
  • White Paper: Financial Fraud Detection with Graph Data Science

    Learn how data scientists and fraud investigators can tap into the power of a graph technology for higher quality predictions in detecting first-party fraud as well as sophisticated fraud rings.

    Read the white paper
  • Neo4j Graph Data Science Sandbox

    Test drive Neo4j Bloom and the GDS Library together with our graph data science sandbox – the fastest way to experiment since there's nothing to install or data to load.

    Try the sandbox
  • AI Standards: Why Graphs Matter

    Neo4j on how graph technology can help guide the development and application of Artificial Intelligence in ways that facilitate innovation and fair competition, public trust and confidence, while incorporating the appropriate protections.

    Read the open letter
  • How Graphs Enhance Artificial Intelligence, with Neo4j's Amy Hodler

    Amy Hodler, Analytics & AI Program Manager at Neo4j, speaks at GraphTour on how graph technology enhances AI, with tactical steps in how to move forward in graph data science.

    Watch video

Business Outcomes

Improve Predictions

Incorporating the predictive power of relationship in advanced analytics and machine learning enables you to continually improve predictive accuracy.

Answer Intractable Questions

raph algorithms are a subset of data science algorithms created to analyze network structures so you can better understand complex systems and answer more complicated questions.

Confidently Operationalize

Using an industry leader to add graph based features to existing data science pipelines is a low-risk way to put more accurate models into production faster.

Challenges

Limited Data

Analytics and machine learning requires a lot of data to increase accuracy but most models today aren’t using their existing data about relationships and network structures.

Iteration

Data science is inherently iterative so it’s essential to use a framework that brings in highly predictive relationships while streamlining the process of moving from data to analysis to visualization and back.

Lack of Scale and Support

Data scientists need enterprise scale, productions features and dedicated data science support that includes packaged and tested algorithms.

Why Neo4j?

Scalable Graph Analytics

Neo4j Graph Data Science library creates a friendly analytics workspace with powerful graph algorithms that can operate over 10’s of billions of nodes and relationships.

Integrated Native Graph Store

Neo4j graph database natively stores interconnected data for persistence and automates data reshaping for analytics.

Intuitive Graph Visualization

Neo4j Bloom enables graph novices and experts to explore results visually, quickly prototype concepts and collaborate with different groups.

Learn More About AI & ML Use Cases

Datanami: Why Knowledge Graphs Are Foundational to Artificial Intelligence
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Computer Business Review: Creating The Most Sophisticated Recommendations Using Native Graphs
More →
Neo4j & Expero, Inc.: Thwart Fraud Using Graph-Enhanced Machine Learning & AI
Watch →
Neo4j Machine Learning Extensions
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David Mack on Medium: Review Prediction with Neo4j and Tensorflow
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Neo4j Blog: Machine Learning, Graphs & the Fake News Epidemic
More →

Ready to get started?

Your enterprise is driven by connections – now it's time for your database to do the same. Click below to download and dive into Neo4j for yourself – or download the Graph Algorithms white paper to learn about these building blocks for better AI context.

Download Neo4j Download the White Paper