Question 360
A Power Platform functional consultant receives this requirement: A trigger's filter was misconfigured and the flow never starts even though the source row is updated. Which TWO complementary steps are appropriate: the recommended configuration action and its most direct independent verification evidence? Select TWO answers.
Explanation
Correct Answers
The required configuration response is: Apply supported Dataverse trigger change type, scope, filtering and trigger conditions, then test qualifying and nonqualifying changes. In this scenario: A trigger's filter was misconfigured and the flow never starts even though the source row is updated. The relevant technical behavior is: Dataverse triggers can be scoped and filtered before downstream actions, reducing irrelevant runs while requiring careful expression and column semantics. The appropriate implementation is: Apply supported Dataverse trigger change type, scope, filtering and trigger conditions, then test qualifying and nonqualifying changes. Independent validation: Inspect trigger configuration, selected columns and conditions, sample changed values and run history including absent runs. Accept only when: Only changes meeting approved criteria start a flow, and relevant updates are not silently excluded.
The most direct evidence is: Inspect trigger configuration, selected columns and conditions, sample changed values and run history including absent runs. In this scenario: A trigger's filter was misconfigured and the flow never starts even though the source row is updated. The relevant technical behavior is: Dataverse triggers can be scoped and filtered before downstream actions, reducing irrelevant runs while requiring careful expression and column semantics. The appropriate implementation is: Apply supported Dataverse trigger change type, scope, filtering and trigger conditions, then test qualifying and nonqualifying changes. Independent validation: Inspect trigger configuration, selected columns and conditions, sample changed values and run history including absent runs. Accept only when: Only changes meeting approved criteria start a flow, and relevant updates are not silently excluded.
Incorrect Answers
This response applies to the different subject of Dataverse business rules scope and validation, rather than directly to Dataverse cloud flow trigger conditions and filtering: Implement business rules with an appropriate scope for supported field validation and behavior, and separately protect server-side data access.. In this scenario: A trigger's filter was misconfigured and the flow never starts even though the source row is updated. The relevant technical behavior is: Dataverse triggers can be scoped and filtered before downstream actions, reducing irrelevant runs while requiring careful expression and column semantics. The appropriate implementation is: Apply supported Dataverse trigger change type, scope, filtering and trigger conditions, then test qualifying and nonqualifying changes. Independent validation: Inspect trigger configuration, selected columns and conditions, sample changed values and run history including absent runs. Accept only when: Only changes meeting approved criteria start a flow, and relevant updates are not silently excluded.
This is an unsafe or unsupported shortcut: Assume a flow that has no run history is always suffering an action-step error rather than a trigger-condition or filter mismatch. It fails to address Dataverse cloud flow trigger conditions and filtering. In this scenario: A trigger's filter was misconfigured and the flow never starts even though the source row is updated. The relevant technical behavior is: Dataverse triggers can be scoped and filtered before downstream actions, reducing irrelevant runs while requiring careful expression and column semantics. The appropriate implementation is: Apply supported Dataverse trigger change type, scope, filtering and trigger conditions, then test qualifying and nonqualifying changes. Independent validation: Inspect trigger configuration, selected columns and conditions, sample changed values and run history including absent runs. Accept only when: Only changes meeting approved criteria start a flow, and relevant updates are not silently excluded.
This response applies to the different subject of Cloud flow trigger types and scheduling decisions, rather than directly to Dataverse cloud flow trigger conditions and filtering: Inspect the trigger type, interval or event subscription, filter conditions and run history after controlled event tests.. In this scenario: A trigger's filter was misconfigured and the flow never starts even though the source row is updated. The relevant technical behavior is: Dataverse triggers can be scoped and filtered before downstream actions, reducing irrelevant runs while requiring careful expression and column semantics. The appropriate implementation is: Apply supported Dataverse trigger change type, scope, filtering and trigger conditions, then test qualifying and nonqualifying changes. Independent validation: Inspect trigger configuration, selected columns and conditions, sample changed values and run history including absent runs. Accept only when: Only changes meeting approved criteria start a flow, and relevant updates are not silently excluded.


