Cloud FlowOrchestrationAdvanced

Data Factory Trigger from Business Event

When a business event occurs — a Dataverse record reaches a state, a file arrives, or an approval completes — the flow starts the right Azure Data Factory pipeline with parameters, waits for completion, and writes results back to the originating record. Bridges business processes to data pipelines.

Azure Data FactoryMicrosoft DataverseMicrosoft Teams

Unique name

FlowLibsDataFactoryTriggerFromBusinessEvent

Publisher

FlowLibs (flowlibs)

Version

1.0.0.0

Components

3 env vars + 1 cloud flow

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What it does

Overview

This flow bridges business processes to data pipelines in Azure Data Factory. When a business event occurs — a Dataverse record reaches a state, a file arrives, or an approval completes — it starts the right pipeline with parameters, waits for completion, and writes results back to the originating record. Data pipelines are usually time-triggered and disconnected from business events; event-driven runs make data processing responsive to what the business is actually doing.

Why you'd use it

Use Case

A business action (for example month-end close, or a new dataset being approved) needs to kick off a data pipeline and have its outcome reflected back on the record that started it. The event-to-pipeline map lets one flow route many event types to the right pipeline without logic changes.

Step-by-step

Flow Architecture

When Business Event Occurs

Dataverse / Approvals / file trigger

Fires on a Dataverse record state change, an approval completion, or a file arrival.

Build Parameters

Compose

Assembles the pipeline run inputs from the business context.

Run Pipeline & Wait

Azure Data Factory - CreateRun

Starts the mapped pipeline via CreateRun and polls GetPipelineRun until the run completes.

Write Back Result

Dataverse - UpdateRecord

Writes the run result/status back onto the originating record.

Solution config

Environment Variables

Schema name	Type	Default	Description
flowlibs_EventPipelineMap	String	{"<event>":"<pipelineName>"}	JSON map of business event key to Data Factory pipeline name.
flowlibs_DataFactoryName	String	REPLACE_WITH_DATA_FACTORY	Azure Data Factory instance that owns the pipelines.
flowlibs_ResultField	String	flowlibs_runresult	Dataverse column the pipeline result/status is written back to.

Auth dependencies

Connectors & Connections

Connector	API name	Actions used
Azure Data Factory	shared_azuredatafactory	CreateRun GetPipelineRun
Microsoft Dataverse	shared_commondataserviceforapps	UpdateRecord
Microsoft Teams	shared_teams	PostMessageToConversation

Note — All connections are referenced as solution connection references; the flow is portable between environments as long as a connection is mapped at import time.

Tweaks & variations

Customization Guide

Almost every realistic variant of this flow can be implemented by changing environment variable values. A few cases require small edits inside the flow definition — those are called out explicitly below.

Idempotency: Guard against duplicate runs per event (e.g. a processed flag or a run key) so the same business event does not start the pipeline twice.
Timeout: Handle long-running pipelines with a polling timeout and a failure branch so the record is not left in a pending state.
Result detail: Store richer pipeline output such as row counts or output paths alongside the status for downstream reporting.

Helpers & literals

Key Expressions

The flow is intentionally light on Power Fx / WDL gymnastics — the heaviest expressions are the branch-name concatenation and the approval outcome check. They are listed below in the order they appear in the flow.

EXPR.01Pipeline lookup

Resolves the pipeline name for the current event from the JSON map env var.

workflow definition language

json(variables('varEventPipelineMap'))?[variables('varEvent')]