Ingest Workday reports

Learn how to ingest Workday reports into Databricks using Lakeflow Connect.

Requirements

To create an ingestion pipeline, you must 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 Workday, you must first complete the steps in Configure Workday reports for ingestion.

Configure networking

If you have serverless egress control enabled, allowlist the host names of your report URLs. For example, the report URL https://ww1.workday.com/service/ccx/<tenant>/<reportName>?format=json has the host name https://ww1.workday.com. See Manage network policies for serverless egress control.

Create an ingestion pipeline

Databricks UI
Databricks Asset Bundles
Databricks notebook

In the sidebar of the Databricks workspace, click Data Ingestion.
On the Add data page, under Databricks connectors, click Workday Reports.
On the Connection page of the ingestion wizard, select the connection that stores your Workday Reports access credentials. If you have the CREATE CONNECTION privilege on the metastore, you can click Create connection to create a new connection with the authentication details in Configure Workday reports for ingestion.
Click Next.
On the Ingestion setup page, enter a unique name for the pipeline.
Select a catalog and a schema to write event logs to. If you have USE CATALOG and CREATE SCHEMA privileges on the catalog, you can click Create schema in the drop-down menu to create a new schema.
Click Create pipeline and continue.
On the Report page, click Add report and enter the report URL. Repeat for each report that you want to ingest.
Click Save and continue.
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, you can click Create schema in the drop-down menu to create a new schema.
Click Save and continue.
(Optional) On the Schedules and notifications page, click Create schedule. Set the frequency to refresh the destination tables.
(Optional) Click Add notification to set email notifications for pipeline operation success or failure, then click Save and run pipeline.

Use Declarative Automation Bundles to manage Workday Reports 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 Declarative Automation Bundles?.

Create a new bundle using the Databricks CLI:
Bash
```
databricks bundle init
```
Add two new resource files to the bundle:
- A pipeline definition file (for example, resources/workday_pipeline.yml). See pipeline.ingestion_definition and Examples.
- A job definition file that controls the frequency of data ingestion (for example, resources/workday_job.yml).
Deploy the pipeline using the Databricks CLI:
Bash
```
databricks bundle deploy
```

Examples

Use these examples to configure your pipeline.

Ingest a single report

The following pipeline definition file ingests a single Workday report:

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

# The main pipeline for workday_dab
resources:
  pipelines:
    pipeline_workday:
      name: workday_pipeline
      catalog: ${var.dest_catalog}
      schema: ${var.dest_schema}
      ingestion_definition:
        connection_name: <workday-connection>
        objects:
          # An array of objects to ingest from Workday. This example ingests a report about all active employees.
          - report:
              source_url: https://wd2-impl-services1.workday.com/ccx/service/customreport2/All_Active_Employees_Data?format=json
              destination_catalog: ${var.dest_catalog}
              destination_schema: ${var.dest_schema}
              destination_table: All_Active_Employees_Data
              table_configuration:
                primary_keys:
                  - Employee_ID

Ingest multiple reports

The following pipeline definition file ingests two Workday reports into separate schemas:

note

Multi-destination pipeline support is API-only. You cannot configure multiple destination schemas from the Databricks UI.

YAML
resources:
  pipelines:
    pipeline_workday:
      name: workday_pipeline
      catalog: my_catalog_1 # Location of the pipeline event log
      schema: my_schema_1 # Location of the pipeline event log
      ingestion_definition:
        connection_name: <workday-connection>
        objects:
          - report:
              source_url: <report-url-1>
              destination_catalog: my_catalog_1
              destination_schema: my_schema_1
              destination_table: my_table_1
              table_configuration:
                primary_keys:
                  - <primary_key_column>
          - report:
              source_url: <report-url-2>
              destination_catalog: my_catalog_2
              destination_schema: my_schema_2
              destination_table: my_table_2
              table_configuration:
                primary_keys:
                  - <primary_key_column>

Bundle job definition file

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

YAML
resources:
  jobs:
    workday_dab_job:
      name: workday_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.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.

Requirements​

Configure networking​

Create an ingestion pipeline​

Examples​

Ingest a single report​

Ingest multiple reports​

Bundle job definition file​

Common patterns​

Next steps​

Additional resources​