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451What is a Graph Database?
452Graph Model: Nodes and Edges
453Property Graphs vs RDF Triples
454When Relationships Are First-Class Citizens
455Index-Free Adjacency
456Graph Query Languages: Cypher and Gremlin
457Use Cases: Social Networks and Recommendations
458Use Cases: Fraud Detection and Knowledge Graphs
459Graph vs Relational Trade-offs
460Neo4j Architecture Overview
461Cypher Query Language Fundamentals
462Creating Nodes and Relationships
463Pattern Matching in Cypher
464Traversal Queries: Friends of Friends
465Variable-Length Paths
466Shortest Path Algorithms
467Filtering and Aggregating Graph Data
468Graph Algorithms: PageRank and Centrality
469Indexes and Query Performance
470Transaction Model and ACID in Neo4j
471Why Graphs: Relationship-Heavy Data Models
472Social Networks and Friend-of-Friend Queries
473Recommendation Engines with Graph Traversal
474Fraud Detection Through Pattern Matching
475Knowledge Graphs and Semantic Networks
476Graph Query Performance Characteristics
477Index-Free Adjacency and Physical Storage
478When Graphs Underperform: Aggregations and Scans
479Hybrid Architectures: Combining Graph and Relational
480Graph Database Scaling Limitations

451What is a Graph Database?
452Graph Model: Nodes and Edges
453Property Graphs vs RDF Triples
454When Relationships Are First-Class Citizens
455Index-Free Adjacency
456Graph Query Languages: Cypher and Gremlin
457Use Cases: Social Networks and Recommendations
458Use Cases: Fraud Detection and Knowledge Graphs
459Graph vs Relational Trade-offs
460Neo4j Architecture Overview
461Cypher Query Language Fundamentals
462Creating Nodes and Relationships
463Pattern Matching in Cypher
464Traversal Queries: Friends of Friends
465Variable-Length Paths
466Shortest Path Algorithms
467Filtering and Aggregating Graph Data
468Graph Algorithms: PageRank and Centrality
469Indexes and Query Performance
470Transaction Model and ACID in Neo4j
471Why Graphs: Relationship-Heavy Data Models
472Social Networks and Friend-of-Friend Queries
473Recommendation Engines with Graph Traversal
474Fraud Detection Through Pattern Matching
475Knowledge Graphs and Semantic Networks
476Graph Query Performance Characteristics
477Index-Free Adjacency and Physical Storage
478When Graphs Underperform: Aggregations and Scans
479Hybrid Architectures: Combining Graph and Relational
480Graph Database Scaling Limitations

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Lesson 474 of 1,919·13. NoSQL: Graph DatabasesPro lesson

Fraud Detection Through Pattern Matching

Detecting fraud rings and suspicious patterns by traversing transaction and entity relationship graphs.

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