Load Dynamics AX data to Microsoft Fabric

Dynamics AX (modernized as Dynamics 365 Finance and Operations) provides RESTful endpoints including OData and JSON-based custom services for data integration and operations. Everything needed to build a working Dynamics AX → Microsoft Fabric pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

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Build your Dynamics AX to Microsoft Fabric pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the Dynamics AX API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

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Dynamics AX API at a glance

These values come from the Dynamics AX API documentation. Check them against the vendor's current reference before relying on them in production.

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How do I authenticate with the Dynamics AX API?

Authentication is performed using OAuth 2.0 with Microsoft Entra ID (formerly Azure AD). Requests must include an 'Authorization' header with a 'Bearer' token obtained from the Microsoft Identity platform.

1. Get your credentials

To obtain credentials for the Dynamics AX (or Dynamics 365 Finance and Operations) REST API, you must use Microsoft Entra ID (formerly Azure Active Directory) authentication. 1. Register a Web Application (Confidential Client) in the Azure Portal via App Registrations. 2. Once registered, copy the Application (Client) ID and the Tenant ID. 3. Generate a Client Secret under the 'Certificates & secrets' section; ensure you copy it immediately, as it cannot be retrieved later. 4. In Dynamics AX, navigate to 'System administration' > 'Setup' > 'Microsoft Entra applications'. 5. Click 'New', enter the Application (Client) ID you generated in Azure, and map it to a specific Dynamics User ID (e.g., a service account) to define the API's permissions.

2. Add them to .dlt/secrets.toml

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[sources.dynamics_ax_source]
client_id = "your_application_client_id"
client_secret = "your_client_secret"
tenant_id = "your_azure_tenant_id"
base_url = "https://your-environment.dynamics.com"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

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What Dynamics AX data can I load into Microsoft Fabric?

These are the Dynamics AX endpoints dlt can load into Microsoft Fabric:

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How do I load only new Dynamics AX records?

Dynamics AX exposes @odata.nextLink on data/Customers, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "customers", "endpoint": {
    "path": "data/Customers",
    "data_selector": "value",
    "incremental": {"cursor_path": "@odata.nextLink", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

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What does the generated Dynamics AX pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading data and metadata from the Dynamics AX API into Microsoft Fabric:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def dynamics_ax_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://<your-instance-url>",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "customers", "endpoint": {"path": "data/Customers", "data_selector": "value"}},
            {"name": "customer_groups", "endpoint": {"path": "data/CustomerGroups", "data_selector": "value"}}
        ],
    }
    yield from rest_api_resources(config)


def load_dynamics_ax_to_fabric() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="dynamics_ax_pipeline",
        destination="fabric",
        dataset_name="dynamics_ax_data",
    )
    load_info = pipeline.run(dynamics_ax_source())
    print(load_info)


if __name__ == "__main__":
    load_dynamics_ax_to_fabric()

Run it with python dynamics_ax_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query Dynamics AX data in Microsoft Fabric?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("dynamics_ax_pipeline").dataset()
df = data.data_entities.df()
print(df.head())

SQL:

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SELECT * FROM dynamics_ax_data.data_entities LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the Dynamics AX to Microsoft Fabric pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw Dynamics AX loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load Dynamics AX data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack