Invoke a downstream process, such as executing a database stored procedure, dataflow, pipeline, or notebook, based on writeback events. Use event triggers to transform data, refresh dependent data, calculate metrics, or start downstream workflows.
Instead of relying on scheduled batch jobs, event triggers turn writeback into a real-time event-driven workflow. Common use cases include:
Executives instantly see consolidated, up-to-date reports without waiting for an end-of-day batch processing run.
Finance teams get immediate visibility into liquidity and bank covenant compliance based on newly entered budget scenarios.
Event triggers can automatically flag the record if a target exceeds its allocated threshold by a set percentage.
Operations can immediately identify potential inventory shortfalls or long-lead component needs based on the latest sales trajectory.
When to use event triggers
Calculations and validations: Run complex server-side business logic or validation routines immediately after user submission.
Data orchestration: Trigger ETL/ELT pipelines to push data into downstream operational systems or data warehouses.
Real-time reporting: Automatically trigger an incremental refresh of a Power BI semantic model so dashboards instantly reflect updated planning entries.
The following table shows the supported trigger types and use cases:
Trigger
Scenario
Writeback initialized
Start a validation or preprocessing pipeline when a budget or forecast writeback begins.
Run a stored procedure to calculate financial metrics such as variance, gross margin, or EBITDA.
Writeback succeeds
Refresh financial reports or consolidate business-unit budgets after a successful writeback.
Trigger a dataflow to move approved forecasts into a downstream reporting or consolidation model.
Recalculate sales targets or forecast metrics using a stored procedure or notebook.
Writeback fails
Trigger an error-handling pipeline to log failed submissions and notify the relevant operations team.
Follow these steps to set up event triggers that automatically kick off a process, such as running a pipeline, in response to a writeback event.
In the Writeback ribbon, select Event Trigger.
To configure your first trigger, select +Add New in the Event Triggers side pane.
Enter a name to uniquely identify the trigger.
Select the event type - you can kick off the downstream process on writeback initialization, success, or failure.
Select the process to trigger from Action Type. See the following sections for configuration details for each process type.
You can pass parameters to stored procedures, notebooks, and pipelines. Select Edit action to configure parameters. You can either enter parameter values or select the Plus (+) icon for built-in options such as Trigger Execution ID, Created By, Created At, Error, and Status.
Select Save. Saving the trigger configuration enables the Test Action option. Use this option to ensure the event trigger is working.
Initiate writeback to kick off the configured event trigger.
Use stored procedure-based event triggers to run complex business logic and recalculate metrics. Trigger a stored procedure to automatically roll up local-level planning entries, convert currencies, and aggregate budgets and forecasts into parent entities for executive-level visibility.
In a Fabric SQL database, create the stored procedure to execute when a writeback is initialized, succeeds, or fails. Refer to the writeback destination table in the stored procedure to consolidate, aggregate, or reconcile data in a planning sheet.
In your planning sheet, select Event Trigger in the Writeback ribbon. Add a new trigger and select Stored Procedure as the Action Type in the event trigger configuration.
Select the Fabric SQL connection and select the database where the stored procedure exists.
Select the schema where the stored procedure created in step 1 resides. Select the stored procedure from the dropdown.
After you select the stored procedure, the Parameters section auto-populates any required parameters. You can enter the parameter values or select them from built-in options by selecting the Plus (+) icon.
In this example, the region and year are user-defined parameters. You use the built-in parameter CreatedBy to capture the user name.
Save the event trigger configuration, then initiate writeback after you receive a success notification that the webhook was added.
Select Trigger Logs in the Writeback ribbon to view details such as the completion status, start time, duration, and stored procedure name.
Pipeline-based event triggers allow you to orchestrate end-to-end data integration workflows whenever writeback events occur. By linking writeback actions directly to Microsoft Fabric data pipelines, you can automatically extract, transform, aggregate, and move planning data across your enterprise systems without waiting for scheduled batch jobs.
This is particularly useful when you need to validate writeback data across multiple sources, combine it with historical actuals, load it into a centralized Data Warehouse or Lakehouse, or trigger conditional multi-step alerts and downstream applications.
Create a Fabric data pipeline with your required downstream activities, such as extracting the writeback data or sending conditional email notifications.
In your planning sheet, select Event Trigger in the Writeback ribbon. Add a new trigger and select Run Pipeline as the Action Type in the event trigger configuration.
Select the pipeline from the OneLake catalog, then choose the Fabric Data Pipeline connection to establish access from your planning sheet.
If your pipeline requires parameters, select Edit action and create the parameters. In this example, you create user-defined parameters to pass the email list and delta load.
Save the event trigger configuration, then initiate writeback after you receive a success notification that the webhook was added.
Select Trigger Logs in the Writeback ribbon to view details such as the completion status, start time, duration, and pipeline name.
Keep your Power BI semantic models automatically aligned with your latest planning data. If you are writing back planning data to your source semantic model, by setting up a semantic model refresh event trigger, writeback updates instantly push through to ensure reports and dashboards reflect up-to-date figures in real time.
In your planning sheet, select Event Trigger in the Writeback ribbon. Add a new trigger and select Refresh Semantic Model from Action Type in the event trigger configuration.
Select your source semantic model from the OneLake catalog and select a Power BI Semantic Model connection.
Optionally pass a request body to set parameters such as commitMode, maxParallelism, retryCount, or timeout. Select Save.
Save the event trigger configuration, then initiate writeback after you receive a success notification that the webhook was added.
Select Trigger Logs in the Writeback ribbon to view details such as the completion status, start time, duration, and semantic model name.
Use dataflow event triggers to automatically clean, transform, or enrich planning data immediately after a writeback. For example, when a regional team submits new forecast entries, a dataflow can instantly run validation logic, adjust currency conversions, or merge writeback entries with historical actuals, ensuring your downstream reporting tables remain clean and fully reconciled without manual intervention or batch delays.
Create a Fabric dataflow with the required data cleansing and transformation logic.
In your planning sheet, select Event Trigger in the Writeback ribbon. Add a new trigger and select Run Dataflow from Action Type in the event trigger configuration.
Select the dataflow to run from the OneLake catalog, then choose the Dataflow connection to establish access from your planning sheet.
Save the event trigger configuration, then initiate writeback after you receive a success notification that the webhook was added.
Select Trigger Logs in the Writeback ribbon to view details such as the completion status, start time, and duration.
Extend your planning capabilities by running code-driven workflows immediately following a writeback event. Use notebooks to:
Pass writeback entries directly into models to predict churn, forecast demand, or detect budget anomalies in real time.
Run custom mathematical algorithms to distribute top-down budget entries down to lower-level SKUs or cost centers.
Append or merge newly submitted planning data directly into Delta tables in OneLake using Spark batch writes.
Create a Fabric notebook to run the required post-processing logic.
In your planning sheet, select Event Trigger in the Writeback ribbon. Add a new trigger and select Run Notebook from Action Type in the event trigger configuration.
Select the notebook you created in step 1 from the OneLake catalog, then choose the Notebook connection to establish access from your planning sheet.
If your pipeline requires parameters, select Edit action and create the parameters. In this example, you pass the region and year as user-defined parameters and use built-in parameters to capture the username and update time.
Save the event trigger configuration, then initiate writeback after you receive a success notification that the webhook was added.
Select Trigger Logs in the Writeback ribbon to view details such as the completion status, start time, and duration.
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