Knowledge Graphs and Master Data

Knowledge Graphs (KGs) are structured representations of knowledge, designed to represent real-world entities and their relationships in a machine-readable format.

Think of them as a vast network of interconnected facts and concepts, providing context and meaning to data. They go beyond simple data storage to capture the 'why' and 'how' behind information.

Knowledge Graphs are built upon a few fundamental components:

• Entities: These are the 'things' in your graph, like people, places, organizations, or concepts. They are typically represented as nodes.
• Relationships: These define how entities are connected or interact. They are represented as directed edges between nodes.
• Properties: Attributes that describe entities or relationships, providing additional detail (e.g., a person's age, a relationship's start date).
• Schema/Ontology: A formal representation of the types of entities, relationships, and properties allowed in the graph, providing structure and rules.