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Data governance often has a reputation for being restrictive and slow. At Credible, we believe governance isn’t achieved by locking things down—it’s achieved by creating a system so powerful, reliable, and easy to use that people want to use it. Our philosophy: make governance the path of least resistance.

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Why Traditional Governance Fails

If your central data platform is slow, inflexible, or confusing, users will find workarounds. This creates a cycle of mistrust and data chaos.
When building their own spreadsheet is faster than waiting for the “official” dashboard, analysts will abandon the central system. This leads to data silos, inconsistent metrics, and mistrust in the numbers. Governance becomes a roadblock to bypass, not a guardrail for safety.
This is more critical in the age of AI. When your AI provides powerful, reliable answers through the governed platform, users have no reason to connect it to insecure spreadsheets or un-vetted data. Good governance becomes the fastest path to getting work done.

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The Pillars of a Governed Platform

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1. Centralized, Code-Based Semantic Models

Define business logic once in version-controlled Malloy models. Every dashboard, user, and AI-generated answer operates from the same verified source of truth—ensuring consistent metrics, relationships, and joins across your organization.

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2. Software Lifecycle for Data Assets

Semantic models and analyses are bundled into versioned packages. This brings the stability and lifecycle management of software engineering to data workflows—manage dependencies, safely update logic, and avoid breaking downstream reports.

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3. Layered Access Control

Application Layer: Role-based permissions (admin, modeler, viewer) control who can access projects, packages, and workspaces. Semantic Layer: Database connections managed at project level ensure queries execute through governed models, not directly against databases. Data Layer: Fine-grained row and field-level security defined in Malloy using #authorize and #bind annotations—version-controlled and fully auditable. See Access Control Overview for details.

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4. Visibility and Lineage

Trust requires transparency. The platform provides a central control plane to:
  • Find the code that defines any metric
  • Trace lineage from source database to final dashboard
  • Understand who is querying what data
  • Optimize your system based on usage analytics

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Next Steps

Access Control Overview

Understand Credible’s permission model

Why Malloy?

Version control and lifecycle management for data models
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