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Ingest data from Veeva Vault

Beta

This feature is in Beta. Workspace admins can control access to this feature from the Previews page. See Manage Databricks previews.

This page shows how to create a managed Veeva Vault ingestion pipeline using Lakeflow Connect.

Requirements​

  • To create an ingestion pipeline, first meet the following requirements:

    • Your workspace must be enabled for Unity Catalog.

    • Serverless compute must be enabled for your workspace. See Serverless compute requirements.

    • If you plan to create a new connection: You must have CREATE CONNECTION privileges on the metastore. See Manage privileges in Unity Catalog.

      If the connector supports UI-based pipeline authoring, an admin can create the connection and the pipeline at the same time by completing the steps on this page. However, if the users who create pipelines use API-based pipeline authoring or are non-admin users, an admin must first create the connection in Catalog Explorer. See Connect to managed ingestion sources.

    • If you plan to use an existing connection: You must have USE CONNECTION privileges or ALL PRIVILEGES on the connection object.

    • You must have USE CATALOG privileges on the target catalog.

    • You must have USE SCHEMA and CREATE TABLE privileges on an existing schema or CREATE SCHEMA privileges on the target catalog.

  • To ingest from Veeva Vault, first configure authentication from Databricks and create a connection. See Configure Veeva Vault for OAuth 2.0 M2M authentication and Create a Veeva Vault connection.

Create an ingestion pipeline​

  1. In the sidebar of the Databricks workspace, click Data Ingestion.

  2. On the Add data page, under Databricks connectors, click Veeva Vault.

  3. On the Connection page of the ingestion wizard, select the connection that stores your Veeva Vault credentials. If you have the CREATE CONNECTION privilege on the metastore, click Plus icon. Create connection to create a connection with the credentials from Configure Veeva Vault for OAuth 2.0 M2M authentication.

  4. Click Next.

  5. On the Ingestion setup page, enter a name for the pipeline.

  6. Select a catalog and a schema to write event logs to. If you have USE CATALOG and CREATE SCHEMA privileges on the catalog, click Plus icon. Create schema in the drop-down menu to create a schema.

  7. Click Create pipeline and continue.

  8. On the Source page, select the objects to ingest.

  9. Click Save and continue.

  10. On the Destination page, select a catalog and a schema to load data into. If you have USE CATALOG and CREATE SCHEMA privileges on the catalog, click Plus icon. Create schema in the drop-down menu to create a schema.

  11. Click Save and continue.

  12. (Optional) On the Schedules and notifications page, click Plus icon. Create schedule. Set the frequency to refresh the destination tables.

    note

    Veeva generates incremental archives every 15 minutes. Scheduling a pipeline to run more frequently than every 15 minutes does not produce additional data.

  13. (Optional) Click Plus icon. Add notification to set email notifications for pipeline operation success or failure, then click Save and run pipeline.

Examples​

Veeva Vault objects are exposed under the default source schema. Ingest individual objects or the entire schema.

Ingest specific objects​

Use this option to ingest a specific subset of objects, or to customize destination naming per object.

The following pipeline definition file ingests individual Veeva Vault objects:

YAML
resources:
  pipelines:
    veeva_vault_pipeline:
      name: veeva_vault_pipeline
      catalog: 'main'
      target: 'veeva_data'
      ingestion_definition:
        connection_name: veeva_vault_connection
        objects:
          - table:
              source_schema: 'default'
              source_table: 'opportunity__v'
              destination_catalog: 'main'
              destination_schema: 'veeva_data'
              destination_table: 'opportunity'
          - table:
              source_schema: 'default'
              source_table: 'account__v'
              destination_catalog: 'main'
              destination_schema: 'veeva_data'
              destination_table: 'account'

Ingest all objects​

Use this option to ingest all Veeva Vault objects into a single destination schema with one declaration.

The following pipeline definition file ingests all supported Veeva Vault objects into a destination schema:

YAML
resources:
  pipelines:
    veeva_vault_pipeline:
      name: veeva_vault_pipeline
      catalog: 'main'
      target: 'veeva_data'
      ingestion_definition:
        connection_name: veeva_vault_connection
        objects:
          - schema:
              source_schema: 'default'
              destination_catalog: 'main'
              destination_schema: 'veeva_data'

Declarative Automation Bundles job definition file​

The following is an example job definition file for use with Declarative Automation Bundles. The job runs daily.

YAML
resources:
  jobs:
    veeva_vault_job:
      name: veeva_vault_job
      schedule:
        quartz_cron_expression: '0 0 0 * * ?'
        timezone_id: 'UTC'
      tasks:
        - task_key: veeva_vault_ingestion
          pipeline_task:
            pipeline_id: ${resources.pipelines.veeva_vault_pipeline.id}

Common patterns​

For advanced pipeline configurations, see Common patterns for managed ingestion pipelines.

Next steps​

Start, schedule, and set alerts on your pipeline. See Common pipeline maintenance tasks.

Additional resources​

On this page