Inside DataBuddy: Why Data Agents Need a Shared Data Foundation
A close reading of DataBuddy's shared data chain, catalog, semantic layer, Agent Harness, and governance model—with a production-oriented POC checklist.
Knowledge path
Data Governance
Why Microsoft Fabric Data Agents Stay Read-Only
Understand the value and limits of read-only analytics through Entra identity, SQL/DAX/KQL routing, Fabric sources, and Purview controls.
The First Step in Enterprise Data Agent Adoption Is Not Model Selection
A staged rollout from a narrow domain and real task set through read-only POC, shadow mode, limited production, and evidence-gated scale.
OpenAI Data Agent Connects Enterprise Data, Dashboards, and Action
OpenAI launched Data Agent in ChatGPT Work. Here is how connectors, business semantics, analytical Skills, dashboards, permissions, and approved actions fit together.
Why Stronger Data Agents Need a Semantic Layer
Schema describes data shape. This guide shows how metrics, entities, dimensions, business rules, and verified examples turn meaning into executable contracts.
The Data Agent Access Layer: Finding the Right Data Before Querying
A practical design for source registration, asset discovery, policy filtering, context packaging, runtime authorization, and access-layer evaluation.
A Seven-Layer Architecture for Production Data Agents
A practical architecture for turning an ambiguous business question into a governed, testable chain of semantics, planning, execution, verification, and delivery.
Data Agent Levels L0–L5: Autonomy Transfers Responsibility
A practical reading of Data Agent levels through initiation, planning, execution, verification, and recovery—not tool count or marketing claims.