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GraphRAG (beyond the hype)
Practical AI
Graphs Illuminate Interconnected Data
Graphs demonstrate their benefits in scenarios with highly interconnected data, such as in medicine, where relationships among patients, symptoms, drugs, and side effects create complex networks. Similarly, in finance, intricate connections between onshore and offshore accounts highlight the need for understanding direct and indirect transactions globally. While relational databases can organize such data in tables, graph databases offer a more intuitive and efficient way to model and analyze these complex relationships. They excel in query construction and pattern recognition, allowing for scalable management and traversal of graph-structured data. The property graph data model, popularized by Neo4j, exemplifies how specialized data structures enhance performance in querying and handling complex joins.
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