What is Knowledge Graph?

Enterprises sit on vast quantities of data locked in silos - CRMs, ERPs, data lakes, spreadsheets, and unstructured documents. A knowledge graph acts as a unifying layer that connects these disparate sources into a single, queryable network.

This connected view enables capabilities that are impossible with traditional databases: intelligent search that understands context, recommendation engines that reason across product catalogues and customer behaviour, and AI systems that can explain their answers by tracing paths through the graph.

Organisations such as Google, Amazon, and the BBC have built knowledge graphs at the core of their platforms. In regulated industries like financial services and pharma, knowledge graphs provide the lineage and traceability that compliance teams require.

At its core, a knowledge graph stores information as triples - subject, predicate, object statements such as “Semantic Partners — provides — Ontology Engineering”. Each entity and relationship is identified by a unique URI, making the data globally unambiguous and linkable.

An ontology defines the schema - the types of entities (classes) and the types of relationships (properties) that are allowed. This gives the graph its structure and enables reasoning: if the ontology says “every Subsidiary is a kind of Organisation”, the graph can infer that facts about organisations also apply to subsidiaries.

Knowledge graphs are typically stored in a triplestore and queried with SPARQL, a powerful graph query language that can traverse relationships of arbitrary depth in a single request.

Financial services: A global bank uses a knowledge graph to map beneficial ownership chains across jurisdictions, enabling automated KYC and anti-money-laundering checks that previously required weeks of manual research.

Pharmaceutical R&D: A drug discovery team links compounds, targets, pathways, and clinical trial results in a knowledge graph, accelerating hypothesis generation and reducing time-to-insight from months to days.

Energy: An oil & gas operator connects well data, sensor readings, and geological models in a knowledge graph built on the OSDU standard, giving engineers a single pane of glass across previously siloed subsurface data.