Connect Workday activity logs directly into Databricks

Use cases

Imagine you need to audit user activity and access in Workday by combining these logs with your enterprise data. With this connector, you can:

• Ingest user activity logs incrementally.
• Use Unity Catalog for data governance.
• Orchestrate ingestion using Databricks Workflows.

How to use

You can create a pipeline using notebooks or Asset Bundles, authenticating via an OAuth refresh token.

from databricks.sdk import WorkspaceClient

w = WorkspaceClient()

# Example of creating an ingestion pipeline
pipeline = w.pipelines.create(
    name="workday_logs_pipeline",
    storage="/Volumes/my_catalog/default/storage_path",
    target="my_catalog.default",
    libraries=[{"notebook": {"path": "/Workspace/Users/admin/workday_notebook"}}]
)

What happens in this code:

1. Initializes the Databricks Workspace client.
2. Creates a new pipeline pointing to a volume and target schema in Unity Catalog.
3. Associates a notebook that executes the ingestion logic.

Limitations and requirements

• Stage: Beta.
• Requires a workspace admin to enable the feature from the Previews page.
• Authentication is supported exclusively via OAuth refresh token.
• Does not support SCD Type 2 or API-based row filtering.

Using it in a pipeline

Raw logs land in the Bronze layer from the Workday connector and can be cleaned and structured in the Silver layer for security and compliance audits.