Asana connector

Important

This feature is in Beta. To use it, a workspace admin must turn on Lakeflow Connect for Asana from the Previews page. See Manage Azure Databricks previews.

The managed Asana connector in Lakeflow Connect ingests work management data such as workspaces, projects, tasks, portfolios, and goals from Asana into Azure Databricks.

Feature availability

Feature	Availability
UI-based pipeline authoring	Supported
API-based pipeline authoring	Supported
Declarative Automation Bundles	Supported
Incremental ingestion	Not supported The connector reingests all records in every table on each pipeline update.
Unity Catalog governance	Supported
Orchestration using Lakeflow Jobs	Supported
API-based column selection and deselection	Supported
API-based row filtering	Not supported
Slowly changing dimension (SCD) type 2	Not supported All tables are ingested as full-refresh snapshots with no change tracking, so SCD type 2 isn't available.
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 user-to-machine (U2M)	Supported
OAuth machine-to-machine (M2M)	Not supported
Basic authentication (username/password)	Not supported
Basic authentication (API key)	Not supported

Ingest from Asana in 3 steps

Note

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

1. Configure Asana for ingestion (Admins): Set up Asana to authenticate with Azure Databricks.
2. Create a Unity Catalog connection (Admins): Create a connection in Catalog Explorer to store credentials for Azure Databricks to authenticate with Asana.
3. Create an ingestion pipeline (Admins or non-admins): Select any supported interface and create a pipeline from an existing connection.