Design a scalable Dataverse model with ownership and controlled change
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Use business concepts, standard tables, explicit relationships, stable identifiers, data ownership, solutions, and separate environments to keep D365 CE data maintainable.
TL;DR
Build D365 CE data models around business concepts, then use standard Dataverse tables where they fit and custom components only for clear needs. Define relationship behaviour, data owners, system-of-record rules, stable integration identifiers, and conflict handling. Document the model, test realistic queries and updates, and deploy changes through solutions across development, test, and production environments.
Original by Softchief Author, on Softchief Technologies. Read the original
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Governance takeaway
- Makers: Check standard tables and relationships before creating custom components, and avoid duplicate fields that can drift from their source.
- Admins/CoE: Maintain a data dictionary, document owners and dependencies, then move tested changes through solutions and separate environments.
- Security/Compliance: Make the owning system, permitted updates, duplicate handling, and sync conflict resolution explicit for each record type.
- Leadership/Business: Confirm business concepts, data owners, and process changes before model changes are released, so the shared model remains usable.
Frequently asked questions
When should Dataverse use an explicit table instead of a many-to-many relationship?
Use an explicit table when the relationship needs details such as status, dates, an owner, or its own review process and lifecycle.
How should D365 CE integrations define record ownership and updates?
Specify which system creates each record type, which fields another system may update, and who resolves duplicates, failed syncs, and conflicts.
How should Dataverse customizations move between development, test, and production environments?
Build and test customizations in separate environments, use solutions to transport components, and review dependencies before deployment.