Explain the concept of a graph data model.

The graph data model is a way of representing and organizing data using graph structures, where data entities are nodes (vertices) and the relationships between them are edges. Key concepts include:

1. **Nodes (Vertices):** Represent entities or objects in the graph, such as people, places, or items.

2. **Edges (Relationships):** Define connections or relationships between nodes. They can be directed (one-way) or undirected (two-way) and may also have properties or weights.

3. **Properties:** Both nodes and edges can have associated attributes or properties that provide additional information about them.

4. **Graph Traversal:** Allows for navigating through the graph by following edges from one node to another. This is useful for querying complex relationships and patterns in the data.

5. **Use Cases:** Particularly suited for scenarios involving complex relationships and connections, such as social networks, recommendation systems, fraud detection, and network analysis.

The graph data model excels at representing and querying data with intricate relationships, offering efficient ways to analyze connections and patterns.