Databricks integration

Connect TheyDo to Databricks to pull warehouse data into your metrics. Once connected, you can write SQL queries against your Databricks tables and surface the results directly on your journeys.

Before you start

  • You need integration-management permission in TheyDo.
  • To set up the integration, you need either Account Admin or Workspace Admin privileges in Databricks.
  • TheyDo uses a Service Principal (a non-human machine account) for secure programmatic access via OAuth 2.0.
  • Make sure your Databricks account has access to the sql and all-apis OAuth scopes:
    • sql — to list and query warehouses
    • all-apis — to support general API operations

If you're unsure about these permissions, contact your workspace admin before starting.

How to set up the Databricks integration

  1. Go to Settings > Integrations in TheyDo.
  2. Find Databricks under Data integrations and select Enable.
  3. Enter an Instance Name — this is how you'll identify this connection in TheyDo.
  4. Click Authorize — this opens a Nango authorization session to complete the OAuth connection with Databricks.
  5. Complete the authorization in the Nango window.
  6. Once done, TheyDo will confirm the connection is Active.

For enterprise teams with advanced security or compliance needs, TheyDo supports connecting Databricks via AWS PrivateLink. This keeps data traffic off the public internet.

  • Requires additional configuration with your DevOps and data team.
  • Implementation may take more time than the standard setup.

If you're interested in PrivateLink, reach out to your Customer Success Manager.

Prepare your data in Databricks

Your Databricks tables need to return the correct columns for each metric type:

Metric type Required columns
CSAT date, positives, negatives, respondents
CES date, respondents, value
NPS date, detractors, promoters, respondents
RATIO date, numerator, denominator
OTHER date, value

Supported data types:

  • Date columns: DATE
  • Metric value columns: INTEGER, FLOAT, or NUMERIC

Column aliasing: If your table uses different column names, use SQL aliasing in your query:

SELECT det AS detractors, ... FROM my_catalog.my_schema.my_table