Idea Recommendation for Managing System Tables in Dataverse
To enhance transparency and control over system tables in Dataverse, I propose a System Table Management Dashboard with built-in tools and clear visibility for users/customers to manage data, solutions, and privileges effectively. For example we have a constantly growing WeResource Base Table, whcih we have to ope a support ticket, in order to Microsoft run a script to delete ophaneted customization records
Key Features and Benefits
1. Transparency of Data
- Data Source Labeling:Every system table should include metadata showing:
- Origin of Data: Which solution (managed/unmanaged) introduced it.
- Purpose: A short description of its role in the system.
- Solution Mapping View: A dashboard that visualizes which tables and components belong to which solution, 1st and 3rd party customizations, solution imports and installed applications metadata.
2. User Privileges and Rights Management
- Granular Permissions: Since Microsoft has defined that the relationship between a user and the data, not the application or environment owners determines access, this functionality should extend to managing system tables.
- Role-Based Management: Customers and administrators should have access to this functionality based on their assigned roles and rights, enabling them to:
- View and manage data associated with system tables.
- Execute cleanup tasks (e.g., removing orphaned customizations).
- Audit Trails: Log all changes made to system tables, including data modifications, schema updates, and deletions, ensuring secure and accountable management.
3. Orphaned Customization Cleanup
- Built-in Cleanup Tool: Replace the existing script-based approach with a user-friendly feature that:
- Identifies orphaned customizations (e.g., unused fields, orphaned records, deprecated tables).
- Provides a preview of items to delete, along with their impact on solutions or applications.
- Allows users to approve deletions directly within the Dataverse UI based on their roles and privileges.
- Impact Assessment: Notify users of dependencies before deletions to prevent accidental system issues.
4. Enhanced Table Documentation
- Each table should have a "Description Tab", where metadata like:
- Creation Date
- Last Modified Date
- Associated Solutions
- Dependency Tree (showing related tables and components)
- User-defined annotations
can be displayed.
5. Customization Validation Reports
- A Validation Tool to:
- Identify conflicting customizations across solutions.
- Highlight unused components for potential cleanup.
6. Open Architecture Approach
- Ensure that all management tools, including cleanup functionalities, are fully accessible through APIs or Admin Center Tools, so customers can integrate them with their workflows if desired.
- Avoid black-box features; instead, provide clear documentation and functionalitoes and transparency on what operations the system performs.
Implementation Roadmap*
1. Phase 1: Data Transparency on Dashboard
2. Phase 2: Cleanup and Validation on Dashboard
3. Phase 3: Privilege Management on Dashboard
4. Phase 4: Documentation and APIs and Tools for all Funtionalities
Expected Outcomes
- Improved Admin/User Confidence: Transparent data and solution management reduce confusion and trust issues.
- Operational Efficiency: Built-in tools for cleanup and validation save time and reduce risks.
- System Integrity and Compliance: Role-based access ensures users and administrators operate within defined rights, upholding system integrity and security. It should be already like that.
By embedding these features into Dataverse and aligning them with Microsoft’s user-role-based access control model, customers and administrators will gain the functionality and transparency needed to manage their environments effectively while staying aligned with modern data governance principles.