Neo4j Graph Data Science is an advanced analytics and machine learning platform designed to analyze relationships in data. It leverages graph algorithms and machine learning models to provide deeper insights, improve predictions, and uncover hidden patterns. The platform integrates seamlessly with data ecosystems, enabling data science teams to quickly move projects into production and share business insights.

Key Features

Graph Algorithms Provides a comprehensive library of graph algorithms for various analyses.

• Centrality measures
• Community detection

Machine Learning Pipelines Supports graph-native machine learning pipelines for predictive modeling.

• Node classification
• Link prediction

Data Ecosystem Integration Seamlessly integrates with various data platforms and tools.

• Apache Spark connector
• Data Warehouse connector

Benefits

Enhanced Data Insights Uncovers hidden patterns and relationships in data.

• Improves prediction accuracy
• Identifies key entities

Operational Efficiency Streamlines data science workflows and project deployment.

• Reduces time to production
• Simplifies model management