Enhance Power BI Copilot Studio documentation

brown9804 · web-flow · commit 441ec7c8d715 · 2025-09-29T13:30:12.000-06:00
Updated the document to include new sections on Fabric data agent concepts, creating a Fabric data agent, and examples of questions to ask. Enhanced the steps for deploying the Fabric MCP Server and configuring the custom connector in Power Platform.
diff --git a/3_PowerPlatform/2_CopilotStudio/2_connecting-PowerBI-CopilotStudio.md b/3_PowerPlatform/2_CopilotStudio/2_connecting-PowerBI-CopilotStudio.md
@@ -20,6 +20,9 @@ Last updated: 2025-07-17
 - [Connect to an existing Model Context Protocol (MCP) server](https://learn.microsoft.com/en-us/microsoft-copilot-studio/mcp-add-existing-server-to-agent) - MCP
 - [Connecting an Agent in Copilot Studio to an MCP Server](https://techcommunity.microsoft.com/blog/microsoft365copilotblog/connecting-an-agent-in-copilot-studio-to-an-mcp-server/4448362) - blog 
 - [Connect AI Agents to Fabric API for GraphQL with a local Model Context Protocol (MCP) server](https://learn.microsoft.com/en-us/fabric/data-engineering/api-graphql-local-model-context-protocol)
+- [Fabric data agent concepts (preview)](https://learn.microsoft.com/en-us/fabric/data-science/concept-data-agent)
+- [How to create a Fabric data agent (preview)](https://learn.microsoft.com/en-us/fabric/data-science/how-to-create-data-agent)
+- [Fabric data agent example with the AdventureWorks dataset (preview)](https://learn.microsoft.com/en-us/fabric/data-science/data-agent-scenario): `This example sets up a Fabric data agent to enable conversational AI over enterprise data`. It connects to a lakehouse with the AdventureWorks dataset and allows users to ask natural language questions. The agent interprets queries, accesses data from sources like warehouses, semantic models, and KQL databases, and returns insights. It simplifies data interaction without requiring code or SQL.
 
 </details>
 
@@ -34,70 +37,95 @@ Last updated: 2025-07-17
 
 <img width="1309" height="944" alt="image" src="https://github.com/user-attachments/assets/c633ed23-55dd-46a0-855b-df11894bd324" />
 
-## Step 1: Prepare Your Environment
-
-Before you begin, make sure you have:
-- Access to **Microsoft Copilot Studio**: https://studio.copilot.microsoft.com
-- Access to **Power Platform**: https://make.powerapps.com
-- A **Power BI dataset** published in **Microsoft Fabric**
-- An **Azure subscription** (for secure deployment)
-- Admin rights to create **custom connectors**
-
-## Step 2: Deploy the Fabric MCP Server
-
-Microsoft provides a Fabric MCP server that supports:
-- Listing workspaces and datasets
-- Executing DAX queries
-- Triggering dataset refreshes 
-
-You can deploy it using Azure Container Apps or run it locally using Docker.
-
-> To deploy:
-1. Clone the official repo:  
-   [Microsoft Fabric MCP GitHub](https://github.com/snahrup/microsoft-fabric-mcp) 
-2. Follow the instructions in the `README.md` for:
-   - Local development
-   - Azure deployment
-   - Authentication setup (OAuth 2.0 recommended)
-
-## Step 3: Create a Custom Connector in Power Platform
-
-1. Go to https://make.powerapps.com
-2. In the left menu:
-   - Click **More** → **Discover all**
-   - Under **Data**, pin **Custom connectors**
-3. Click **Custom connectors** → **New custom connector** → **Create from blank**
-4. Name your connector (e.g., `FabricMCPConnector`) → Click **Continue**
-
-## Step 4: Configure the Connector
-1. Toggle **Swagger editor**
-2. Paste the OpenAPI (Swagger) YAML from the MCP repo:
-   - Replace `dummyurl.azurewebsites.net` with your deployed MCP server URL
-3. Click **Create connector**
-
-## Step 5: Add the MCP Connector to Copilot Studio
-
-1. Go to https://studio.copilot.microsoft.com
-2. Open your **agent**
-3. Go to **Tools** → **Add a tool**
-4. Choose **Model Context Protocol (MCP)**
-5. Fill in:
-   - **Name**: Fabric MCP
-   - **Description**: Connects to Power BI datasets via Fabric
-   - **Server URL**: `https://your-mcp-server-url/mcp`
-6. Choose **Authentication**:
-   - Use **OAuth 2.0** with Azure AD App credentials
-7. Click **Create**
-
-## Step 6: Test the Integration
-
-1. In Copilot Studio, create a **topic** like “Ask about sales data”
-2. Use the MCP tool to invoke:
-   - `tools/list` → to list available datasets
-   - `tools/query` → to run DAX queries
-3. Validate responses and format them using adaptive cards or plain text
+## Prepare your data
 
+> [Medallion Architecture](./AzurePortal/1_MedallionArch/): Explore the structured approach to data management.
 
+ <div align="center">
+   <img src="https://github.com/user-attachments/assets/2c5141ea-4f3a-4054-b8bd-313efde24ff0" alt="Centered Image" style="border: 2px solid #4CAF50; border-radius: 2px; padding: 2px; width: 900px; height: auto;"/>
+ </div>
+
+> Or if you need to handle `complex data transformations and large-scale data processing`, you can use our combined solution of **Fabric + Databricks**. This powerful combination leverages the strengths of both platforms to provide a robust data processing pipeline. This workshop on [Fabric with Databricks for Data Analytics](https://microsoft.github.io/TechExcel-Fabric-with-Databricks-for-Data-Analytics/) offers a comprehensive step-by-step guide on developing Medallion Architecture using Fabric and Databricks. <br/>
+
+<p align="center">
+  <img width="650" alt="image" src="https://github.com/user-attachments/assets/58431d3b-e294-46fe-89a4-92a046168ec4" />
+</p>
+
+Click [here to read more about Azure Databricks + Fabric](https://github.com/MicrosoftCloudEssentials-LearningHub/DemosScenarios-TechTalks/blob/main/0_Azure/2_AzureAnalytics/3_Databricks/1_demos/0_MedallionArch_Fabric%2BDatabricks/README.md) `better together`
+
+## Use Fabric Data Agent (Preferred for Semantic Models)
+
+> AI skills in Microsoft Fabric enable users to `create conversational AI experiences that answer questions about data stored
+> in lakehouses, warehouses, Power BI semantic models, and KQL databases`. These skills make data insights accessible and
+> actionable, allowing users to `interact with data naturally and receive relevant answers without needing technical expertise`.
+> You can create custom Q&A systems using generative AI, guiding the AI with instructions and examples to ensure it understands your organization's context and data.
+
+Key Features:
+
+- Customizable Q&A Systems: Tailor the AI to answer specific questions relevant to your organization.
+- Generative AI: Leverage advanced AI to interact with your data, enhancing data-driven decision-making.
+- Ease of Use: Once set up, users can simply ask questions and get accurate answers without needing deep technical knowledge.
+
+E.g: 
+
+<img width="1886" height="831" alt="image" src="https://github.com/user-attachments/assets/79f455c8-da0e-4187-b370-f98aff2985ed" />
+
+<img width="1897" height="837" alt="image" src="https://github.com/user-attachments/assets/3e92d177-c0e6-456c-b965-980aff12a16d" />
+
+<details>
+<summary><b> Setup required</b> (Click to expand)</summary>
+
+1. Please ensure you read all the [prerequisites](https://learn.microsoft.com/en-us/fabric/data-science/how-to-create-data-agent#prerequisites)
+2. **Tenant switch enabled**: These features must be activated as mentioned here [prerequisites](https://learn.microsoft.com/en-us/fabric/data-science/how-to-create-data-agent#prerequisites)
+ 
+    <https://github.com/user-attachments/assets/f0df6fb9-e139-4c97-9b68-a6ea05eb6584>
+
+3. **F2 Fabric capacity or higher**: Ensure you have the appropriate Fabric capacity.
+4. **Workspace configured with Fabric Capacity**:
+
+    <img width="200" height="300" alt="image" src="https://github.com/user-attachments/assets/7fbfb16d-a32a-4540-bd03-e6b3c0412a5b">
+
+    <img width="700" height="300" alt="image" src="https://github.com/user-attachments/assets/1cb31d49-6138-4c95-835a-a61ccb08661b">
+
+5. At least one of these: A warehouse, a lakehouse, one or more Power BI semantic models, or a KQL database with data.
+
+</details>
+
+<details>
+<summary><b> How it works (Click to expand)</summary>
+
+1. Go to the `workspace`, click on `+ New item`, search for `Data agent`, and select it.
+
+    <img width="550" alt="image" src="https://github.com/user-attachments/assets/42ff0a1c-3e61-4e24-8bb5-e56db6fe9b7e" />
+
+2. Choose the name for the Data agent instance:
+   
+     <https://github.com/user-attachments/assets/752734e4-f7f6-44a3-8ccb-069ac005a410>
+
+3. Add data:
+   
+     <https://github.com/user-attachments/assets/9800e74e-cbca-45ff-a712-bb2e8a095bb5>
+
+4. Relate tables, and start asking!
+
+     <img width="550" alt="image" src="https://github.com/user-attachments/assets/77d5ddbe-8230-440d-9617-d937da48b3cd" />
+
+</details>
+
+> [!NOTE]
+> Or use: MCP Server (For Custom Integrations) you create it and connect via Power Platform for example.
+
+## Examples of what to ask 
+
+| **Question**                                                                 | **Example of it looks**                                                                                       |
+|------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------|
+| **Data Exploration**                                                         |                                                                                                               |
+| - Can you provide an overview of this dataset?  <br/> - Are there any missing values or anomalies in this dataset?                               |            <img width="500" alt="image" src="https://github.com/user-attachments/assets/2a43117e-3b29-46f8-98b7-f097df425429">                                                                                                    |
+|  What are the key variables in this data?                                   |       <img width="500" alt="image" src="https://github.com/user-attachments/assets/621c6237-7c79-4c67-981a-e9d7afccf29f">                    |
+| **Data Insights**                                                            |                                                                                                               |
+| What patterns or trends can you identify in this data?                     |<img width="500" alt="image" src="https://github.com/user-attachments/assets/899653c3-fa41-4834-8606-37759a7f1ad6">               |
+| Can you highlight any correlations between variables?                      | <img width="500" alt="image" src="https://github.com/user-attachments/assets/a9442f38-ade1-45ee-9cb6-4adf8bdbf0f7">              |
+| What are the outliers in this dataset?                                     | <img width="500" alt="image" src="https://github.com/user-attachments/assets/1c0d07b2-91fe-4335-9760-886c10e77bb9">                 |
 
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