Governance
How Credible makes governance the path of least resistance
Data governance has a reputation for being restrictive and slow — the review board that takes three weeks, the locked-down warehouse nobody can query. At Credible, we believe governance works by making the governed path faster and easier than working around it — so people choose it.
Our philosophy: make governance the path of least resistance.
Why Traditional Governance Fails
If the central data platform is slow, inflexible, or confusing, users route around it. When building a private spreadsheet is faster than waiting for the official dashboard, analysts abandon the central system — and the organization inherits data silos, inconsistent metrics, and mistrust in the numbers. Governance becomes a roadblock to bypass, not a guardrail for safety.
AI raises the stakes in both directions. An ungoverned agent pointed at raw data produces confident, wrong answers at scale. But a governed agent — one that answers through vetted data models, quickly and reliably — removes the reason to bypass governance at all. When the governed path is also the best path, good governance becomes the fastest way to get work done.
How Credible Governs
In Credible, governance is built into how models are defined, published, accessed, and observed, not layered on top as a policy document.
Definitions Live in Code
Business logic is defined once, in version-controlled Malloy models. Every dashboard, workspace chat, and AI-generated answer operates from the same verified source of truth — consistent metrics, relationships, and joins across the organization. Because the model is code, changes go through the same discipline as software: reviewed in pull requests, tested in CI, and traceable to an author.
Data Assets Have a Software Lifecycle
Models, data apps, and their manifest ship together as versioned packages, with the same atomic publishing, auto-promote, and auto-archive lifecycle described in Architecture — so updating logic never breaks downstream consumers mid-flight.
Access Is Controlled at Every Level
- Permissions — Role-based permissions govern who can do what: environment roles (Admin, Modeler, Viewer) control modeling and publishing, while workspace and document sharing control analysis. See Permissions.
- Connections — Database credentials are stored once, in the environment, and never leave it. Modelers and developers SSO into Credible and work against managed connections — no credentials on laptops, no shared service accounts. Every query is proxied through Credible, access-checked, and logged. See Environments.
- Data — Row- and column-level security is defined in the model itself with
#(authorize), secure givens, and field access modifiers — version-controlled, auditable, and enforced identically on every surface, from workspace chat to MCP agents to the REST APIs. See Access Control.
Because every consumer goes through the same governed data model, there is exactly one enforcement point. There's no BI tool with its own permissions to drift out of sync, and no API path that skips the rules.
Everything Is Visible
Because all consumption routes through one gateway, Credible gives you a single place to find the code that defines any metric and to trace lineage from source database to final answer. That same gateway is what makes compliance, cost, and model quality observable — see One Gateway for how the audit trail, the cost and latency data, and the feedback loop all follow from it.