Workiva connector

Important

This feature is in Beta. Workspace admins can control access to this feature from the Previews page by opting into the Lakeflow Connect for Workiva preview. See Manage Azure Databricks previews.

The managed Workiva connector in Lakeflow Connect allows you to ingest audit activity, users, and roles from Workiva into Azure Databricks.

Feature availability

Feature	Availability
UI-based pipeline authoring	Supported
API-based pipeline authoring	Supported
Declarative Automation Bundles	Supported
Incremental ingestion	Supported The activities table only. users and roles are ingested as full snapshots.
Unity Catalog governance	Supported
Orchestration using Databricks Lakeflow Jobs	Supported
API-based column selection and deselection	Not supported
API-based row filtering	Not supported
SCD Type 2	Not supported
Automated schema evolution: New and deleted columns	Supported
Automated schema evolution: Data type changes	Not supported
Automated schema evolution: Column renames	Not supported Requires a full refresh.

Authentication methods

Authentication method	Availability
OAuth U2M	Not supported
OAuth M2M	Supported Workiva OAuth2 client credentials (client ID and client secret).
Basic authentication (username/password)	Not supported
Basic authentication (API key)	Not supported

Ingest from Workiva in 3 steps

Note

Before starting, review the Azure Databricks user persona, supported interfaces, ingestion frequency, and common patterns.

1. Configure Workiva for ingestion (Admins) — Create a Workiva OAuth2 application and obtain a client ID and client secret to authenticate with Azure Databricks.
2. Create a Unity Catalog connection (Admins) — Create a connection in Catalog Explorer so non-admins can create pipelines.
3. Create an ingestion pipeline (Admins or non-admins) — Select any supported interface and create a pipeline from an existing connection.