Documenting Azure Machine Learning

The Azure Machine Learning connector imports metadata from Azure Machine Learning into Dataedo, including:

• Machine Learning models (Model Containers)
• Model versions (Model Version Resources)
• Datasets
• Dataset versions

Dataedo connects to an Azure ML workspace, retrieves metadata for registered models and their versions, and imports them as documentation objects.

Additionally, in the Source Description field, the connector automatically generates:

• Model Card – for a model
• Model Version Card – for a specific version of a model

Both cards are generated as HTML using dedicated templates from the connector.

---

Structure of the Model Card Template (Model Container)

The Model Card for MachineLearningModelContainerResource includes the following sections:

1. Header

   • title (model name)
   • created by
   • created at
   • last updated

2. Description

   • model description
   • or No description

3. Latest Version

   • latest version number/name
   • or No version

4. Tags

   • table of model-level tags:
     • Key
     • Value

Structure of the Model Version Card Template (Model Version Resource)

The Model Version Card for MachineLearningModelVersionResource includes detailed metadata about a single version:

1. Header

   • model name
   • version
   • resource ID
   • status (provisioning state)
   • stage
   • model type
   • created at
   • created by (+ type)
   • last updated
   • modified by (+ type)
   • job name

2. Description

   • version description
   • or No description

3. Tags

   • table of version tags:
     • Key
     • Value

4. Properties

   • table of custom properties:
     • Key
     • Value
   • or No custom properties

5. Parameters

   • parameters extracted from the associated job (if available)
   • table:
     • Key
     • Value
   • or No parameters

---

Connecting to Azure Machine Learning

Importing Metadata in Dataedo Portal

Entry point

caution

This action can be performed only by users with the Connection Manager role

Navigate to:

Connections → Add new connection → Azure Machine Learning

This will open the import wizard.

Step 1. Connection details

info

A Connection in Dataedo represents a saved configuration for accessing a data source.
It can be reused for future imports and scheduling.

Provide the required connection details: Connection name, Subscription ID, Resource Group, and Workspace Name.

Optionally, you may also add a description to provide additional context.

You can also customize the Display name, which can be helpful for easier identification in the future.

Step 2. Credentials

Choose your credentials from the list of the already saved ones, or add new ones using the New credentials button.

Step 3. Objects to import

For each selected database, you can choose which objects to import:

• Select object types.

• Use Advanced filters to include or exclude objects with name patterns

Step 4. Schedule

caution

You must configure at least one import task in the schedule section.
If you skip this, an empty database will be created and no metadata will be imported.

Configure scheduling options for each source individually:

• Define tasks you want to schedule (Metadata Import, Data Quality run, Refresh Profiling)
• Run daily, on selected weekdays, or on specific days of the month
• Choose an exact time of execution
• Task state:
  • Active – the task will run as scheduled
  • Draft – the task is saved but not executed until switched to Active
• Run immediately – when checked, the task will also be executed right after clicking Create connection

useful tip

Only one source in a metadata import can have Run immediately selected.

---

Limitations

• Dataedo does not import Execution or Prompt objects. The metadata of Run objects is part of the Model Version Card documentation, but they are not separate objects.
• Datasets do not contain information about their columns or their sources, and lineage is not built.
• Model versions do not contain information about input or output parameters.

Specification

Imported metadata

	Imported	Editable
Model	✅	✅
Model Card (Source Description)	✅
Model Version	✅	✅
Model Version Card (Source Description)	✅
Dataset	✅	✅
Dataset Version	✅	✅