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Ingest data from Workday HCM

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 Workday Human Capital Management (HCM) ingestion pipeline using Lakeflow Connect.

Requirements​

  • To create an ingestion pipeline, you must first:

    • 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.

      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 Workday HCM, you must first complete the steps in Configure authentication to Workday HCM.

Create an ingestion pipeline​

Each source table is ingested into a streaming table. For a list of supported source tables, see Supported data.

Use Databricks Asset Bundles to manage Workday HCM pipelines as code. Bundles can contain YAML definitions of jobs and tasks, are managed using the Databricks CLI, and can be shared and run in different target workspaces (such as development, staging, and production). For more information, see What are Databricks Asset Bundles?.

  1. Create a new bundle using the Databricks CLI:

    Bash
    databricks bundle init

  2. Add two new resource files to the bundle:

    • A pipeline definition file (resources/workday_hcm_pipeline.yml). See pipeline.ingestion_definition and Examples.
    • A job definition file that controls the frequency of data ingestion (resources/workday_hcm_job.yml).

  3. Deploy the pipeline using the Databricks CLI:

    Bash
    databricks bundle deploy

Examples​

Use these examples to configure your pipeline.

Ingest a single source table​

The following pipeline definition file ingests a single source table:

YAML
variables:
  dest_catalog:
    default: main
  dest_schema:
    default: ingest_destination_schema

# The main pipeline for workday_hcm_dab
resources:
  pipelines:
    pipeline_workday_hcm:
      name: workday_hcm_pipeline
      catalog: ${var.dest_catalog}
      schema: ${var.dest_schema}
      ingestion_definition:
        connection_name: <workday-hcm-connection>
        objects:
          # An array of objects to ingest from Workday HCM. This example ingests the workers table.
          - table:
              source_schema: default
              source_table: workers
              destination_catalog: ${var.dest_catalog}
              destination_schema: ${var.dest_schema}

Ingest multiple source tables​

The following pipeline definition file ingests multiple source tables:

YAML
variables:
  dest_catalog:
    default: main
  dest_schema:
    default: ingest_destination_schema

# The main pipeline for workday_hcm_dab
resources:
  pipelines:
    pipeline_workday_hcm:
      name: workday_hcm_pipeline
      catalog: ${var.dest_catalog}
      schema: ${var.dest_schema}
      ingestion_definition:
        connection_name: <workday-hcm-connection>
        objects:
          # An array of objects to ingest from Workday HCM.
          - table:
              source_schema: default
              source_table: workers
              destination_catalog: ${var.dest_catalog}
              destination_schema: ${var.dest_schema}
          - table:
              source_schema: default
              source_table: payroll
              destination_catalog: ${var.dest_catalog}
              destination_schema: ${var.dest_schema}

Bundle workflow file​

The following is an example job definition file to use with Databricks Asset Bundles. The job runs every day, exactly one day from the last run.

YAML
resources:
  jobs:
    workday_hcm_dab_job:
      name: workday_hcm_dab_job

      trigger:
        periodic:
          interval: 1
          unit: DAYS

      email_notifications:
        on_failure:
          - <email-address>

      tasks:
        - task_key: refresh_pipeline
          pipeline_task:
            pipeline_id: ${resources.pipelines.pipeline_workday_hcm.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​