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Explore advanced Amazon Neptune capabilities for high-performance graph analytics and queries over data lakes in this 41-minute conference talk from AWS re:Invent 2025. Discover how to unlock implicit and explicit relationships in your data to drive more accurate and trustworthy generative AI responses through knowledge graphs built from both structured and unstructured data. Learn to combine graph algorithms including PageRank, Louvain clustering, and path optimization with semantic search capabilities, while executing Cypher queries on Parquet and Iceberg formats stored in Amazon S3. Examine code samples and benchmarks demonstrating advanced architectures that leverage Neptune for multi-hop reasoning, entity linking, and context enrichment at scale. Master techniques for building knowledge graphs that enhance generative AI applications by providing rich contextual information and relationship mapping across your data lake infrastructure. Note that this session requires prior familiarity with graph concepts and data lake architectures.
