NODES 2024 - LLM-Assisted Data Exploration With the Neo4j Runway Python Library

In this session, Alex Gilmore will guide you through how to use the Neo4j Runway Python library to explore your relational data as a graph. Runway abstracts communicate with LLMs to assist in data discovery and graph data model generation. It also provides methods to import data models from other tools, such as arrows.app, and automatically generate ingestion code. It can also easily load your data into Neo4j. Get certified with GraphAcademy: https://dev.neo4j.com/learngraph Neo4j AuraDB https://dev.neo4j.com/auradb Knowledge Graph Builder https://dev.neo4j.com/KGBuilder Neo4j GenAI https://dev.neo4j.com/graphrag