Glossary
Enterprise data and AI terms
Practical definitions for the concepts behind governed data access. Written for IT professionals, data teams, and enterprise architects working with Microsoft Dataverse, Power Platform, and AI systems.
Data Access Templates
Predefined, governed data operations that carry business logic, table relationships, and access rules into reusable units. Consumers select a template and supply parameters instead of writing or generating queries.
Data Governance
The set of policies, processes, and controls that ensure enterprise data is accurate, consistent, secure, and used appropriately. In practice, it determines who can access what data, under what rules, and with what audit trail.
Deterministic Execution
A data access approach where the same input always produces the same output. In contrast to AI-generated queries, deterministic execution uses predefined templates to guarantee consistent, predictable results.
Microsoft Power Platform
A suite of low-code tools from Microsoft, including Power Apps, Power BI, Power Automate, Power Pages, and Copilot Studio, built on top of Microsoft Dataverse for building apps, automating workflows, and deploying AI agents.
Model Context Protocol (MCP)
An open standard for connecting AI systems to external data sources, tools, and services. MCP provides a standardized interface so AI tools can access data without proprietary connectors.
Semantic Data Layer
An abstraction layer between enterprise data sources and the consumers that use them. It translates database complexity into business terms, applies governance rules, and provides consistent, trusted answers.
Text-to-SQL
An AI approach that converts natural language questions into SQL database queries. While powerful for ad-hoc exploration, text-to-SQL faces accuracy challenges on complex enterprise data.
See these concepts in action
Learn how dhino applies these principles to give enterprises a single governed data layer for people, systems, and AI.