Overview

Organisations are investing heavily in data platforms and AI, yet many still struggle to get consistent answers to simple questions like: “What is revenue?” or “Who is a customer?”.

 

The issue occurs in traditional BI and in Gen AI where the model generates different answers to the same question. The root issue is rarely the technology but the lack of a shared layer of meaning that connects business language to technical data.

 

Traditional approaches often fail because definitions live in slide decks, spreadsheets, or individual dashboards. Metrics get recreated repeatedly, data becomes inconsistent across teams, and AI initiatives stall due to poor context, unclear terminology, and unreliable information.

 

Our offering solves this by designing and building a semantic layer of business-ready metrics & governed models and/or an ontology of formal domain concepts & relationships so your organisation can scale analytics and AI with confidence and without losing control of definitions, quality, or accountability.

What Is Semantic Layer & Ontology Accelerator?

A service that creates a shared language for your data by translating raw technical structures into business concepts, metrics, and rules that are reusable across BI, AI, and data products. This can include a BI focused semantic model (e.g., Power BI/Fabric/Databricks Metric Views/Tabular/dbt metrics), a domain ontology (for knowledge graphs, AI reasoning, or semantic search), or both depending on your needs.

What it enables:

  • Consistent metrics across teams (single source of truth)
  • Reusable, governed data models for reporting and self-service analytics
  • Clear business definitions backed by traceable logic and ownership
  • AI-ready context (entities, relationships, and terminology for retrieval and reasoning)
  • Reduced duplication in dashboard and data product development

This can be business analysis or development led. We can help define and implement models, measures, governance, and adoption practices so the semantic layer is used in day-to-day decision making depending on requirements.

Why Semantics & Ontologies Are Critical

A semantic foundation is what makes data scalable, trustworthy, and usable especially when you’re moving beyond dashboards into automation and AI. Without it, organisations spend more time reconciling numbers and discussing definitions than acting on insights, in addition AI initiatives fail due to inconsistent definitions and missing context.

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Common challenges

  • Different teams have different definitions of the same metric e.g., “margin”, “utilisation”, “active customer”
  • Dashboards proliferate with duplicate logic and conflicting results
  • Data catalogues exist, but business meaning isn’t operationalised
  • AI tools can access data, but don’t understand context entities, relationships, terminology and deliver inconsistent results
  • Governance becomes a blocker because standards aren’t embedded into models and workflows

A robust semantic layer and ontology can help you move from data availability to data reliability and AI readiness.

What’s Included in Our Semantic Layer & Ontology Accelerator

Professional Services
01 Discovery & Semantic Assessment

- Identify priority domains, key metrics, and decision journeys - Assess existing models, toolset, definitions, catalogues and duplication hotspots - Define scope (semantic layer, ontology, or combined approach)

01 Discovery & Semantic Assessment
02 Business Glossary & Metric Standardisation

- Define core entities (Customer, Product, Matter, Asset, Order, etc.) - Agree metric definitions, calculation logic, and accountability - Establish naming standards, hierarchies, and reference data rules

02 Business Glossary & Metric Standardisation
03 Semantic Layer Development (BI / Metrics Layer)

- Build governed semantic models and reusable measures - Implement dimensional structures, hierarchies, and conformed dimensions - Apply security design patterns (RLS/OLS where required)

03 Semantic Layer Development (BI / Metrics Layer)
Data-driven decisions
04 Ontology Design & Knowledge Graph Foundations

- Define domain ontology (concepts, relationships, constraints) - Map ontology to data sources and metadata - Enable semantic search, entity resolution, and AI retrieval patterns

04 Ontology Design & Knowledge Graph Foundations
Resilience and cybersecurity
05 Governance, Operating Model & Adoption

- Define ownership model for definitions and change control - Certification approach for assets example gold/silver/bronze - Enablement including documentation, training, and handover

05 Governance, Operating Model & Adoption
06 Deliverables / Outputs

- Semantic model(s) implemented and deployed - Data catalogue - Ontology artefacts (where in scope) and lineage documentation - Governance playbook (roles, workflow, quality rules) - Adoption toolkit

06 Deliverables / Outputs
Blue & Purple Abstract pattern

Benefits of Semantic Layer & Ontology Accelerator

Get one version of the truth

Reduce reconciliations and disputes by standardising metrics and definitions in a governed layer.

Scale self-service without losing control

Enable more users to build insights safely using certified measures and consistent business logic.

Accelerate reliable and consistent AI outcomes

Give AI the “meaning layer” it needs: entities, relationships, definitions, and traceable logic to deliver consistent reliable results.

Increase productivity by reducing duplication

Stop rebuilding the same calculations across dashboards and teams reuse becomes the default.

Improve governance and compliance

Embed ownership, lineage, and security into the semantic artefacts reducing risk.

Why Choose Telefónica Tech

Proven delivery expertise

We have delivered semantic models and domain foundations across sectors, aligning business stakeholders and technical teams.

Structured approach

A repeatable approach that balances domain discovery, engineering quality, governance, and adoption.

Business alignment first

We prioritise decision journeys and value based metric selection ensuring outcomes map to real operational needs and deliver a return on investment.

End-to-end capability

From data platform to governance to BI and AI enablement one partner across the full lifecycle.

Start Your Semantic Layer & Ontology Journey

If you’re asking: “How do we ensure our analytics and AI solutions use consistent, trusted definitions and deliver reliable responses?”

 

The answer starts with a semantic foundation designed with the business and engineered for scale. Book a session with Telefónica Tech today.


Frequently Asked Questions

A semantic layer is a business-friendly abstraction over data that standardises metrics, definitions, hierarchies, and relationships so reports and users get consistent answers. 

Ontology development defines domain concepts (entities), relationships, and rules in a structured way it is often used for knowledge graphs, semantic search, and AI reasoning and helps ensure reliable responses. 

Without a shared meaning, metrics drift, dashboards conflict, and AI lacks context to get consistent and reliable answers from organisations data. A semantic foundation improves trust, reuse, and scalability.

A focused domain semantic layer can take 2–6 weeks. An enterprise program or ontology-enabled approach typically takes 6–12+ weeks, depending on scope and complexity. 

Typically: faster reporting cycles, consistent metrics, improved self-service adoption, lower duplication, and stronger AI readiness through better context. 

Not always, semantic models suit BI and metrics standardisation. Ontologies are most valuable when you need richer relationships, semantic search, knowledge graphs, or AI reasoning across domains. We can review what you have during the initial discovery and tailor the engagement. 

We have built them in Databricks and Fabric.

Team investigating cyber threats using Databricks Lakewatch security analytics platform