Overview
A business ontology is a structured model of the things a business cares about (its people, assets, events and processes) and of how those things relate to one another. In analytics, an ontology links these business concepts to the data that represents them, so people and AI can work with data in business terms rather than technical ones.
In Grafieks, you build an ontology entity-first: you define the business entities, assign a semantic-layer data source to each one, and then connect the entities through relationships.
Why ontology matters
Section titled “Why ontology matters”Business data usually lives in many systems, each described in its own technical structure. Most users think in terms of customers, orders and invoices, not tables and columns. An ontology closes that gap by:
- Presenting data as business concepts people already understand.
- Keeping information connected across systems, teams and domains.
- Giving everyone a shared vocabulary for discussing performance and results.
Core concepts
Section titled “Core concepts”| Concept | What it means |
|---|---|
| Entity | A business object or event that matters to your organization, such as Customer, Product, Account, Employee, Order or Service Request. |
| Relationship | A meaningful link between two entities, such as Customer places Order or Invoice records Payment. |
| Semantic layer | The governed data source that supplies the data for an entity. Each entity is assigned the most relevant semantic layer. |
| Ontology | The complete model of entities and relationships that describes how a business works, shared across teams and domains. |
Example: connecting a business across teams
Section titled “Example: connecting a business across teams”The relationships below are illustrative and span sales, finance and operations:
| From | Relationship | To |
|---|---|---|
| Customer | places | Order |
| Order | includes | Product |
| Order | billed through | Invoice |
| Invoice | records | Payment |
| Product | managed by | Department |
The same approach adapts to other contexts, for example accounts and claims, patients and appointments, suppliers and purchases, or projects and resources.
How ontology helps AI
Section titled “How ontology helps AI”An ontology gives AI a map of business entities and their relationships. Instead of guessing where to look, AI can follow relevant paths across entities and semantic layers to investigate a question.
For example, in a logistics scenario, AI can start with a question about delayed shipments and follow connected entities (delivery exceptions, vehicles, drivers and routes) to identify a likely contributing cause, such as a road closure. In general, this involves three moves:
- Start with a business question and identify the relevant entities.
- Trace relationships to compare possible contributing factors.
- Use the connected evidence to surface a likely root cause.
Ontology vs. semantic layer
Section titled “Ontology vs. semantic layer”The two work together but do different jobs.
| Ontology | Semantic layer | |
|---|---|---|
| Describes | Business concepts and how they relate | The governed data behind those concepts |
| Role in Grafieks | Defines entities and relationships | Serves as the data source assigned to each entity |
| Scope | Can connect many semantic layers in one model | Typically covers a domain such as Sales, Finance or Operations |
Benefits
Section titled “Benefits”- Make data understandable. Users see business concepts rather than technical data structures.
- Keep context connected. Information from different systems is related in a way that reflects how work, records and outcomes fit together.
- Support consistent decisions. Teams share a common vocabulary for exploring performance and discussing results.
- Give AI better context. AI can trace connected evidence across entities and semantic layers.
Who can use it
Section titled “Who can use it”Ontology is not tied to one industry or function. It can model entities, processes and relationships for any industry, business domain or department, for example customers and orders in sales, accounts and invoices in finance, or products and locations in operations.
What is a business ontology in analytics? A structured model of the concepts, entities, events and relationships a business cares about. It connects those business ideas to the data that represents them.
Can an ontology use more than one semantic layer? Yes. You model entities first, then assign a semantic-layer data source to each. Different entities in the same ontology can use different semantic layers and still be connected through business relationships.
What is the difference between an ontology and a semantic layer? An ontology describes business concepts and how they relate. In Grafieks, you assign a semantic layer as the data source for each entity.
Can an ontology support different industries and departments? Yes. Grafieks Ontology can model entities, processes and relationships for any industry, domain or department.
How does an ontology help AI find business insights? It gives AI a map of entities and relationships, so AI can follow paths across entities and semantic layers to trace contributing factors and highlight meaningful insights.