How microsoft/fabric-samples works
Microsoft Fabric Samples is a collection of independent, documentation-oriented examples rather than one application. The represented workflows include authenticated GraphQL queries and display, Unity Catalog shortcut synchronization, CSV/Parquet-to-table examples, and a staged customer-churn analysis. The README also describes feature and community samples, but those directories are not present in the supplied tree. Notebook stage links follow the explicit filenames; unsampled implementations and other sample wiring are not inferred.
Main entry points: util.py Shortcut sync workflow · App.js Authenticated React app · App.tsx Apollo customer app · Client.ts Apollo client setup
Components 22
GraphQL samples
- Authenticated React app
docs-samples/data-engineering/GraphQL/React/src/App.js - Profile display
docs-samples/data-engineering/GraphQL/React/src/components/ProfileData.jsx - Fabric GraphQL API
- Apollo customer app
docs-samples/data-engineering/GraphQL/React-Apollo-TS/src/App.tsx - Apollo client setup
docs-samples/data-engineering/GraphQL/React-Apollo-TS/src/Client.ts - Contoso charts and table
docs-samples/data-engineering/GraphQL/React-App-Contoso/client/src/App.js - Contoso GraphQL proxy
docs-samples/data-engineering/GraphQL/React-App-Contoso/Server/index.js - C# GraphQL client
docs-samples/data-engineering/GraphQL/C#/sample-graphql-app.cs - GraphQL MCP server
docs-samples/data-engineering/GraphQL/MCP/FabricGraphQL_MCP.js
Lakehouse data
- CSV table example
docs-samples/data-engineering/createTablefromCSV.py - Parquet to Delta
docs-samples/data-engineering/createTablefromParquet.py - Fabric lakehouse
- Shortcut sync workflow
docs-samples/onelake/unity-catalog/util.py - Databricks Unity Catalog
- Fabric shortcuts API
Churn analysis
- Ingest churn data
docs-samples/data-science/enrich-powerbi-report-with-machine-learning/Bank Customer Churn Analysis/Bank Customer Churn Analysis/00 - Ingest Churn Data as Semantic Model.Notebook/notebook-content.py - Explore semantic model
docs-samples/data-science/enrich-powerbi-report-with-machine-learning/Bank Customer Churn Analysis/Bank Customer Churn Analysis/01 - Explore the Semantic Model with Semantic Link.Notebook/notebook-content.py - Build churn model
docs-samples/data-science/enrich-powerbi-report-with-machine-learning/Bank Customer Churn Analysis/Bank Customer Churn Analysis/02 - Build a Churn Prediction Model.Notebook/notebook-content.py - Score active customers
docs-samples/data-science/enrich-powerbi-report-with-machine-learning/Bank Customer Churn Analysis/Bank Customer Churn Analysis/03 - Batch Scoring on Active Customers.Notebook/notebook-content.py - Power BI semantic model
Other components
- Sample user
- MCP tool caller
Connections 22
- Sample user → Authenticated React app: uses
- Authenticated React app → Fabric GraphQL API: queries
- Authenticated React app → Profile display: renders results
- Sample user → Apollo customer app: uses
- Apollo customer app → Apollo client setup: creates client
- Apollo client setup → Fabric GraphQL API: sends requests
- Sample user → Contoso charts and table: views
- Contoso charts and table → Contoso GraphQL proxy: fetches data
- Contoso GraphQL proxy → Fabric GraphQL API: queries
- Sample user → C# GraphQL client: runs
- C# GraphQL client → Fabric GraphQL API: sends query
- MCP tool caller → GraphQL MCP server: calls tools
- GraphQL MCP server → Fabric GraphQL API: introspects or queries
- CSV table example → Fabric lakehouse: writes table
- Parquet to Delta → Fabric lakehouse: writes Delta
- Shortcut sync workflow → Databricks Unity Catalog: lists tables
- Shortcut sync workflow → Fabric lakehouse: reads shortcuts
- Shortcut sync workflow → Fabric shortcuts API: creates or deletes
- Ingest churn data → Power BI semantic model: creates model
- Explore semantic model → Power BI semantic model: explores
- Build churn model → Power BI semantic model: uses data
- Score active customers → Power BI semantic model: scores customers