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Govern Data Access

Situation: Business users frequently request reference data exports from IT teams. You want to enable independent access while maintaining appropriate control and governance.

What we need to achieve: Self-service data access with proper governance, reducing IT bottlenecks and empowering business users.

When to use this approach

  • Frequent requests for reference data exports.

  • Business users who need current data for reports and analysis.

  • Existing governed reference data that’s ready for broader access.

  • Clear understanding of who should have what level of access.

Implementation path

Step 1: Set up role-based access

Understand the access levels:

Role Capabilities

Viewer

Read-only access to published data.

Editor

Everything a Viewer can do, as well as manage records (add, edit, delete, or import in bulk) and submit them for review.

Approver

Everything an Editor can do, as well as approve and reject changes, publish records directly, and manage validation rules on the table.

Owner

Everything an Approver can do, as well as full table management — rename, delete, share, edit description, and modify the schema.
Implementation tasks:

  1. Review current access: Set Up Access and Governance - Understand role-based permissions.

  2. Assign appropriate roles to users or groups based on their responsibilities.

  3. Train users on their access levels and capabilities.

For scaling self-service access, grant roles to user groups rather than to individuals. New team members inherit the right access automatically when added to the group.

Step 2: Publish to Catalog

Make data discoverable and accessible:

Implementation tasks:

  1. Publish your tables: Work with Published Reference Data - Enable platform-wide access.

  2. Add clear descriptions so users understand what data is available.

  3. Set up search tags to improve discoverability.

Step 3: Enable self-service workflows

Establish clear processes:

Implementation tasks:

  1. Document access request procedures for users who need higher-level access.

  2. Create usage guidelines explaining what data can be used for what purposes.

  3. Set up monitoring to track usage patterns and ensure compliance.

Step 4: Support business users

Ensure successful adoption:

Implementation tasks:

  1. Train users on how to find and access data in the Catalog.

  2. Provide clear contact information for data-related questions.

  3. Establish feedback mechanisms to improve the self-service experience.

Common use cases after implementation

  • Business reporting: Users access current exchange rates, product categories, and regulatory codes for reports.

  • Data analysis: Analysts use geographic regions, demographic categories, and risk ratings for studies.

  • System integration: Applications programmatically access lookup tables and validation standards.

Next steps

  • Monitor and optimize: Track usage patterns and gather feedback to improve the self-service experience.

  • Scale your approach: Best Practices - Patterns for rolling out across your organization.

  • Improve data quality: Use Reference Data for DQ Validation - Use reference data to validate other datasets.

  • Explore other scenarios: Common Use Cases - Get inspiration from other real-world scenarios.

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