Graph analytics is the process of examining relationships and connections within data represented as a graph. In a graph, entities such as people, devices, locations, or transactions are represented as nodes, while their relationships are represented as edges. Analyzing these connections can reveal patterns that may be difficult to identify in traditional tables.
Graph analytics is used in social networks, fraud detection, cybersecurity, recommendation systems, supply chains, and knowledge management. Techniques can identify highly connected entities, important relationships, communities, unusual connections, and paths between nodes. For example, a financial institution can analyze connections between accounts and transactions to uncover suspicious relationship patterns. By examining how entities interact rather than viewing them independently, graph analytics helps organizations understand complex networks and make more informed decisions.
