This session offers valuable insights from our experience transforming a RAG (Retrieval Augmented Generation) Proof of Concept, which utilizes a Neo4j knowledge graph, into a fully-fledged cloud application. This session is designed to provide practical guidance on enhancing your development practices and optimizing Neo4j-based applications for the cloud environment.
During the workshop, the team will delve into several key areas, including:
- Prioritizing Development: Discover strategies for efficiently prioritizing development tasks to ensure your project advances smoothly from concept to production.
- Moving Code out of Jupyter Notebooks: Learn the best practices for transitioning code from Jupyter Notebooks to a more structured and scalable environment suitable for cloud application development.
- Creating Ingestion Pipelines: Gain insights into designing and implementing effective ingestion pipelines that streamline the flow of data into your Neo4j knowledge graph, enhancing data reliability and availability.
- Refactoring the Graph Data Model: Explore techniques for refining and optimizing your graph data model to better support the scalability and performance requirements of cloud applications.
Trainers: Daniel Bukowski, Alex Gilmore & Alexander Fournier
