# microsoft/fabric-samples architecture

> Architecture diagram of the GitHub repository microsoft/fabric-samples, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-27). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/microsoft/fabric-samples
- Repository: https://github.com/microsoft/fabric-samples

## Overview

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: [`docs-samples/onelake/unity-catalog/util.py`](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/onelake/unity-catalog/util.py) (Shortcut sync workflow), [`docs-samples/data-engineering/GraphQL/React/src/App.js`](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React/src/App.js) (Authenticated React app), [`docs-samples/data-engineering/GraphQL/React-Apollo-TS/src/App.tsx`](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React-Apollo-TS/src/App.tsx) (Apollo customer app), [`docs-samples/data-engineering/GraphQL/React-Apollo-TS/src/Client.ts`](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React-Apollo-TS/src/Client.ts) (Apollo client setup)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_graphql["GraphQL samples"]
  node_reactapp["Authenticated React app<br/>[App.js]"]
  node_reactprofile["Profile display<br/>[ProfileData.jsx]"]
  node_fabricgraphql{{"Fabric GraphQL API"}}
  node_apolloapp["Apollo customer app<br/>[App.tsx]"]
  node_apolloclient["Apollo client setup<br/>[Client.ts]"]
  node_contosoui["Contoso charts and table<br/>[App.js]"]
  node_contosoproxy["Contoso GraphQL proxy<br/>[index.js]"]
  node_csharpclient["C&#35; GraphQL client"]
  node_mcpserver["GraphQL MCP server"]
end

subgraph group_lakehouse["Lakehouse data"]
  node_csvingest["CSV table example"]
  node_parquetingest["Parquet to Delta"]
  node_lakehouse[("Fabric lakehouse")]
  node_syncjob["Shortcut sync workflow<br/>[util.py]"]
  node_unitycatalog[("Databricks Unity Catalog")]
  node_fabricapi{{"Fabric shortcuts API"}}
end

subgraph group_datascience["Churn analysis"]
  node_notebookingest["Ingest churn data"]
  node_notebookexplore["Explore semantic model"]
  node_notebookmodel["Build churn model"]
  node_notebookscore["Score active customers"]
  node_semanticmodel[("Power BI semantic model")]
end

node_user(("Sample user"))
node_mcpuser(("MCP tool caller"))

node_user -->|"uses"| node_reactapp
node_reactapp -->|"queries"| node_fabricgraphql
node_reactapp -->|"renders results"| node_reactprofile
node_user -->|"uses"| node_apolloapp
node_apolloapp -->|"creates client"| node_apolloclient
node_apolloclient -->|"sends requests"| node_fabricgraphql
node_user -->|"views"| node_contosoui
node_contosoui -->|"fetches data"| node_contosoproxy
node_contosoproxy -->|"queries"| node_fabricgraphql
node_user -->|"runs"| node_csharpclient
node_csharpclient -->|"sends query"| node_fabricgraphql
node_mcpuser -->|"calls tools"| node_mcpserver
node_mcpserver -->|"introspects or queries"| node_fabricgraphql
node_csvingest -->|"writes table"| node_lakehouse
node_parquetingest -->|"writes Delta"| node_lakehouse
node_syncjob -->|"lists tables"| node_unitycatalog
node_syncjob -->|"reads shortcuts"| node_lakehouse
node_syncjob -->|"creates or deletes"| node_fabricapi
node_notebookingest -->|"creates model"| node_semanticmodel
node_notebookexplore -->|"explores"| node_semanticmodel
node_notebookmodel -->|"uses data"| node_semanticmodel
node_notebookscore -->|"scores customers"| node_semanticmodel

click node_reactapp "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React/src/App.js"
click node_reactprofile "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React/src/components/ProfileData.jsx"
click node_apolloapp "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React-Apollo-TS/src/App.tsx"
click node_apolloclient "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React-Apollo-TS/src/Client.ts"
click node_contosoui "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React-App-Contoso/client/src/App.js"
click node_contosoproxy "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React-App-Contoso/Server/index.js"
click node_csharpclient "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/C%23/sample-graphql-app.cs"
click node_mcpserver "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/MCP/FabricGraphQL_MCP.js"
click node_csvingest "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/createTablefromCSV.py"
click node_parquetingest "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/createTablefromParquet.py"
click node_syncjob "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/onelake/unity-catalog/util.py"
click node_notebookingest "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-science/enrich-powerbi-report-with-machine-learning/Bank%20Customer%20Churn%20Analysis/Bank%20Customer%20Churn%20Analysis/00%20-%20Ingest%20Churn%20Data%20as%20Semantic%20Model.Notebook/notebook-content.py"
click node_notebookexplore "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-science/enrich-powerbi-report-with-machine-learning/Bank%20Customer%20Churn%20Analysis/Bank%20Customer%20Churn%20Analysis/01%20-%20Explore%20the%20Semantic%20Model%20with%20Semantic%20Link.Notebook/notebook-content.py"
click node_notebookmodel "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-science/enrich-powerbi-report-with-machine-learning/Bank%20Customer%20Churn%20Analysis/Bank%20Customer%20Churn%20Analysis/02%20-%20Build%20a%20Churn%20Prediction%20Model.Notebook/notebook-content.py"
click node_notebookscore "https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-science/enrich-powerbi-report-with-machine-learning/Bank%20Customer%20Churn%20Analysis/Bank%20Customer%20Churn%20Analysis/03%20-%20Batch%20Scoring%20on%20Active%20Customers.Notebook/notebook-content.py"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_reactapp,node_reactprofile,node_fabricgraphql,node_apolloapp,node_apolloclient,node_contosoui,node_contosoproxy,node_csharpclient,node_mcpserver,node_user toneBlue
class node_csvingest,node_parquetingest,node_lakehouse,node_syncjob,node_unitycatalog,node_fabricapi toneAmber
class node_notebookingest,node_notebookexplore,node_notebookmodel,node_notebookscore,node_semanticmodel toneMint
class node_mcpuser toneIndigo
```

## Components

### GraphQL samples

- [Authenticated React app](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React/src/App.js): `docs-samples/data-engineering/GraphQL/React/src/App.js`
- [Profile display](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React/src/components/ProfileData.jsx): `docs-samples/data-engineering/GraphQL/React/src/components/ProfileData.jsx`
- **Fabric GraphQL API**
- [Apollo customer app](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React-Apollo-TS/src/App.tsx): `docs-samples/data-engineering/GraphQL/React-Apollo-TS/src/App.tsx`
- [Apollo client setup](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React-Apollo-TS/src/Client.ts): `docs-samples/data-engineering/GraphQL/React-Apollo-TS/src/Client.ts`
- [Contoso charts and table](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React-App-Contoso/client/src/App.js): `docs-samples/data-engineering/GraphQL/React-App-Contoso/client/src/App.js`
- [Contoso GraphQL proxy](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/React-App-Contoso/Server/index.js): `docs-samples/data-engineering/GraphQL/React-App-Contoso/Server/index.js`
- [C# GraphQL client](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/C%23/sample-graphql-app.cs): `docs-samples/data-engineering/GraphQL/C#/sample-graphql-app.cs`
- [GraphQL MCP server](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/GraphQL/MCP/FabricGraphQL_MCP.js): `docs-samples/data-engineering/GraphQL/MCP/FabricGraphQL_MCP.js`

### Lakehouse data

- [CSV table example](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/createTablefromCSV.py): `docs-samples/data-engineering/createTablefromCSV.py`
- [Parquet to Delta](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-engineering/createTablefromParquet.py): `docs-samples/data-engineering/createTablefromParquet.py`
- **Fabric lakehouse**
- [Shortcut sync workflow](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/onelake/unity-catalog/util.py): `docs-samples/onelake/unity-catalog/util.py`
- **Databricks Unity Catalog**
- **Fabric shortcuts API**

### Churn analysis

- [Ingest churn data](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-science/enrich-powerbi-report-with-machine-learning/Bank%20Customer%20Churn%20Analysis/Bank%20Customer%20Churn%20Analysis/00%20-%20Ingest%20Churn%20Data%20as%20Semantic%20Model.Notebook/notebook-content.py): `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](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-science/enrich-powerbi-report-with-machine-learning/Bank%20Customer%20Churn%20Analysis/Bank%20Customer%20Churn%20Analysis/01%20-%20Explore%20the%20Semantic%20Model%20with%20Semantic%20Link.Notebook/notebook-content.py): `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](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-science/enrich-powerbi-report-with-machine-learning/Bank%20Customer%20Churn%20Analysis/Bank%20Customer%20Churn%20Analysis/02%20-%20Build%20a%20Churn%20Prediction%20Model.Notebook/notebook-content.py): `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](https://github.com/microsoft/fabric-samples/blob/main/docs-samples/data-science/enrich-powerbi-report-with-machine-learning/Bank%20Customer%20Churn%20Analysis/Bank%20Customer%20Churn%20Analysis/03%20-%20Batch%20Scoring%20on%20Active%20Customers.Notebook/notebook-content.py): `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

- 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