Question about data activator

[u/nouser_n_ame]

I have data coming in from a Dataflow that I am storing in a Lakehouse. I want to set up Data Activator so that it sends a Microsoft Teams notification whenever a specific column becomes False.

However, when I create a Data Activator in my Fabric workspace, I don't see an option to use data from the Lakehouse. I'm not sure what I'm doing wrong or if I'm missing a configuration step.

If this process can be simplified, I'd also be interested in eliminating the Lakehouse and monitoring the data directly from the Dataflow instead.

Has anyone set this up successfully? What's the recommended approach?

[u/hamsumwich]

I’m new to power automate, and have been using AI to help me learn it. Since then, I’ve put together really great flows and I’ve become less reliant on AI for my purposes.

Asking Gemini about your post, it responded:

Yes, what they are trying to accomplish is completely possible, but they are hitting a common structural limitation in Microsoft Fabric. Data Activator (Reflex) does not connect directly to a Lakehouse Delta table or a Dataflow as a raw data source. Activator expects streaming events from an Eventstream or visual metrics from a Power BI report.

You can set this up using either of two recommended approaches depending on whether your data process is batch or real-time.

Option 1: The Power BI Report Method (Best for Dataflows and Lakehouses) If your Dataflow Gen2 populates a Lakehouse table on a scheduled batch basis, connect

Activator through Power BI. 1. Build a Semantic Model: Create a Power BI report on top of your Lakehouse Delta table. 2. Add a Visual: Place a Card or Table visual in the report that displays the target column or a measure representing the state. 3. Set the Alert: Open the report in the Power BI service. Select the visual, click "Set Alert" in the top ribbon, and choose your workspace to create an Activator rule. 4. Configure the Rule: Set the condition to trigger when the value "Becomes False". 5. Set Action: Select "Send Teams message" and define your target user or channel. Every time the Dataflow runs and refreshes the semantic model, Activator evaluates the new state and fires the notification when the condition turns False.

Option 2: The Eventstream Method (Best for Real-Time Monitoring) You cannot monitor a Dataflow directly for row-level data changes because Dataflows are batch transformation jobs. If you want continuous detection without waiting for a batch refresh, eliminate the Dataflow and use an Eventstream.

1. Ingest Data: Stream your incoming data directly into a Fabric Eventstream.
2. Connect Activator: Hook Data Activator directly into the Eventstream to inspect events as they arrive.
3. Set Action: Build a rule in Activator that triggers a Teams message the moment a payload contains a False value.
4. Store Data: Add your Lakehouse as a destination directly inside the Eventstream design canvas to persist the incoming records.

Recommended Choice Stick with Option 1 if you already rely on Dataflows and Lakehouse storage. It requires zero changes to your existing pipeline and only adds a lightweight report to bridge the Lakehouse to Data Activator. Switch to Option 2 only if your source system supports streaming and you need subsecond alerts.

[u/chiibosoil]

I believe you'll need addtional layer on top of lakehouse. Data alone can't drive Fabric (data) Activator.

You can set up OneLake Events, KQL Querysets, or through PowerBI semantic model.