How to Build an Amazon Scale Knowledge Graph for GraphRAG

In this Community Call, we are joined by Graph.Build. They'll take the 2023 Amazon Reviews dataset - 571M+ reviews with second-level timestamps, rich item metadata (price, images, attributes) and “bought-together” link graphs - and show the steps of turning it into a governed property knowledge graph. With a GraphRAG layer on top, you can ask questions like: “Why did ratings drop for Model X in Sept 2023?” or “Which accessories are most often co-purchased by similar cohorts, and what explanations do power users give?”. What we’ll cover / what you’ll learn: - Model & Build: Designing an enterprise-ready graph model (users ↔ reviews ↔ items ↔ ‘bought-together’ links), mapping semi-structured and structured sources in Graph.Build - Schema: Generating Memgraph-ready schema and ingesting into database - GraphRAG in Practice: How to set up a GraphRAG pipeline on Memgraph on top of the Amazon Reviews dataset About Memgraph: Memgraph offers a light and powerful graph platform comprising the Memgraph Graph Database, MAGE Library, and Memgraph Lab Visualization. Memgraph is a dynamic, lightweight graph database optimized for analyzing data, relationships, and dependencies quickly and efficiently. It comes with a rich suite of pre-built deep path traversal algorithms and a library of traditional, dynamic, and ML algorithms tailored for advanced graph analysis, making Memgraph an excellent choice in critical decision-making scenarios such as risk assessment (fraud detection, cybersecurity threat analysis, & criminal risk assessment), 360-degree data and network exploration [Identity and Access Management (IAM), Master Data Management (MDM), & Bill of Materials (BOM)], and logistics and network optimization. Website: https://www.memgraph.com Twitter: https://www.twitter.com/memgraphdb LinkedIn: https://www.linkedin.com/company/memgraph Facebook: https://www.facebook.com/memgraph