Microsoft Dynamics 365 Customer Experience Analyst : Use the Dataverse connector in a cloud flow
The Dataverse connector in a cloud flow enables seamless integration between Microsoft Power Automate and your Dataverse environment, allowing you to automate business processes and manage data efficiently. With this connector, you can create, read, update, or delete rows in Dataverse tables directly from a flow, as well as trigger flows when data changes (such as when a row is added, modified, or deleted). It supports both standard and custom tables, making it versatile for a variety of business scenarios. By leveraging the Dataverse connector, organizations can streamline operations, enforce business rules, and ensure data consistency across applications, all while reducing manual effort and improving productivity.
- Actions such as Add a new row, Update a row, Delete a row, Get a row by ID, List rows, and Invoke a bound/unbound action let a flow write to and retrieve from Dataverse tables.
- Triggers (like When a row is added, modified, or deleted) allow flows to run automatically in response to data changes.
- Orchestrate processes – e.g., create approvals or notifications when data changes in Dataverse.
- Synchronize systems – automatically replicate or update records between Dataverse and external apps (SharePoint, SQL, Dynamics 365, etc.).
- Enforce business logic – combine with conditions, expressions, or parallel branches in a flow to execute precise actions based on Dataverse content.
- When a row is added, modified, or deleted
- When a flow step is requested from Dataverse
- Add a new row
- Update or delete a row
- Get a row by ID
- List rows with filters, sorting, or pagination
- Invoke bound or unbound actions on a table
- When you configure a step in Power Automate, the connector generates an OData call to the Dataverse Web API.
- Authentication is handled through Azure Active Directory (AAD), ensuring that only users with proper Dataverse permissions can access data.
- You can use standard tables (like Accounts or Contacts) or custom tables you’ve created.
- Automation: Send notifications when a record is created or updated.
- Data integration: Sync data between Dataverse and external systems (e.g., SharePoint, SQL Server, Dynamics 365).
- Business logic: Use flow conditions, approvals, or loops to act on Dataverse data automatically.
- Record maintenance: Clean up or transform rows across tables at scale.
- Apply filters (e.g., via `Filter Query`) in “List rows” to avoid retrieving large datasets unnecessarily.
- Use pagination for bulk data.
- Respect security roles—flows run with the owner’s permissions.
- Combine Dataverse actions with other connectors to build complete, end-to-end processes.
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