Glossary
What is a semantic data layer?
A semantic data layer is an abstraction layer between enterprise data sources and the consumers that use them. Instead of giving people, systems, or AI direct access to databases, a semantic data layer translates database complexity into business terms, applies governance rules, and provides consistent, trusted answers.
Think of it as a contract. The data layer promises: "Ask me for active customers and you will always get the same definition, the same logic, and the same access controls, regardless of who or what is asking."
Why enterprises need a semantic data layer
Without a semantic data layer, every consumer of enterprise data has to solve the same problems independently. The marketing team writes one query to count active customers. Finance writes a different one. The AI copilot generates a third. All three return different numbers.
This is not a data quality problem. The data is fine. The problem is that business logic, access rules, and definitions are scattered across individual queries, reports, and integrations instead of being encoded in a single shared layer.
A semantic data layer solves this by establishing business definitions once and enforcing them everywhere. "Active customer" means the same thing whether a person asks in a report, a system requests it via API, or an AI assistant surfaces it in a conversation.
How a semantic data layer works
Three principles that make a semantic data layer work in practice.
Abstraction
Consumers interact with business concepts ("quarterly revenue," "active accounts") rather than database tables, joins, and SQL. The complexity stays hidden.
Governance
Access controls, audit trails, and business rules are applied at the layer, not reimplemented by each consumer. Security is a property of the data access, not an afterthought.
Consistency
Business definitions are established once and shared across all consumers. Whether a person, system, or AI asks the same question, they get the same answer.
How dhino implements a semantic data layer
dhino is a semantic data layer built for enterprises using Microsoft Dataverse and the broader Power Platform ecosystem. It uses templates to define business logic, relationships, and guardrails, then serves that data to any consumer through deterministic execution.
This architecture separates understanding from execution. An AI assistant or business user interprets what is being asked (non-deterministic). dhino executes the predefined, governed logic to deliver the answer (deterministic). The result: no hallucinations on business-critical data.
Fetch gives business users direct access to the semantic layer for segmentation, reports, and data exports.
dhino Trust connects AI tools like Microsoft Copilot to the semantic layer for trusted, deterministic answers.
Integrate routes system-to-system data flows through the semantic layer with full governance.
Publish exposes the semantic layer to external audiences through governed API endpoints.
See a semantic data layer in action
Learn how dhino gives enterprises a single governed layer for all data consumers: people, systems, and AI.