Ingest Workday reports

Learn how to ingest Workday reports into Azure 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 Create a Workday Reports connection.

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

  1. In the sidebar of the Azure Databricks workspace, click Data Ingestion.
  2. On the Add data page, under Databricks connectors, click Workday Reports.
  3. 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 Plus icon. Create connection to create a new connection with the authentication details in Create a Workday Reports connection.
  4. Click Next.
  5. On the Ingestion setup page, enter a unique 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, you can click Plus icon. Create schema in the drop-down menu to create a new schema.
  7. Click Create pipeline and continue.
  8. On the Report page, click Plus icon. Add report and enter the report URL. Repeat for each report that you want 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, you can click Plus icon. Create schema in the drop-down menu to create a new 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.
  13. (Optional) Click Plus icon. Add notification to set email notifications for pipeline operation success or failure, then click Save and run pipeline.

Declarative Automation Bundles

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?.

  1. Create a bundle using the Databricks CLI:

    databricks bundle init
    
  2. 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).
  3. Deploy the pipeline using the Databricks CLI:

    databricks bundle deploy
    

Databricks notebook

  1. Import the following notebook into your Azure Databricks workspace:

    Get notebook

  2. Leave cell one as-is.

  3. Modify cell three with your pipeline configuration details. See pipeline.ingestion_definition and Examples.

  4. Click Run all.

Examples

Use these examples to configure your pipeline.

Ingest a single report

The following pipeline definition file ingests a single Workday report:

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 Azure Databricks UI.

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>

Ingest incrementally, starting from a fixed date

Important

Incremental ingestion is in Beta. For limitations, see Incremental ingestion.

The following example ingests a report incrementally starting from 2025-02-01, lagging one day behind the current date. sequence_by specifies the cursor column, and workday_report_parameters.parameters maps the XML aliases of your Workday prompts to filter expressions. The start filter uses coalesce(current_offset(), date(...)) to resume from the last cursor value on subsequent runs, or fall back to the start date on the first run.

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

resources:
  pipelines:
    pipeline_workday:
      name: workday_pipeline
      catalog: ${var.dest_catalog}
      schema: ${var.dest_schema}
      ingestion_definition:
        connection_name: <workday-connection>
        objects:
          - report:
              source_url: https://wd2-impl-services1.workday.com/ccx/service/customreport2/<report-name>?format=json
              destination_catalog: ${var.dest_catalog}
              destination_schema: ${var.dest_schema}
              destination_table: <destination-table>
              table_configuration:
                primary_keys:
                  - <primary_key_column>
                sequence_by:
                  - <cursor_column>
                workday_report_parameters:
                  parameters:
                    <Start_Filter_XML_Alias>: '{coalesce(current_offset(), date("2025-02-01"))}'
                    <End_Filter_XML_Alias>: '{current_date() - INTERVAL 1 DAY}'

Ingest incrementally using a rolling window

Important

Incremental ingestion is in Beta. For limitations, see Incremental ingestion.

The following example always re-ingests the last 30 days on every run by setting both filters relative to current_date() with no coalesce.

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

resources:
  pipelines:
    pipeline_workday:
      name: workday_pipeline
      catalog: ${var.dest_catalog}
      schema: ${var.dest_schema}
      ingestion_definition:
        connection_name: <workday-connection>
        objects:
          - report:
              source_url: https://wd2-impl-services1.workday.com/ccx/service/customreport2/<report-name>?format=json
              destination_catalog: ${var.dest_catalog}
              destination_schema: ${var.dest_schema}
              destination_table: <destination-table>
              table_configuration:
                primary_keys:
                  - <primary_key_column>
                sequence_by:
                  - <cursor_column>
                workday_report_parameters:
                  parameters:
                    <Start_Filter_XML_Alias>: '{current_date() - INTERVAL 30 DAY}'
                    <End_Filter_XML_Alias>: '{current_date()}'

Declarative Automation Bundles job definition file

Declarative Automation Bundles

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.

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.

Supported expressions for prompt parameters

When configuring incremental ingestion, the workday_report_parameters prompt values must use supported expression syntax. Arbitrary expressions are not supported.

Supported primitives:

  • current_date() — Today's date at pipeline start, in YYYY-MM-DD format.
  • date("YYYY-MM-DD") — A fixed date. Must use YYYY-MM-DD format.
  • current_date() - INTERVAL N DAY or date("...") - INTERVAL N DAY — Subtracts N days from a date. N must be a positive integer. Only DAY is supported (not WEEK, MONTH, etc.). Only subtraction (-) is supported.
  • coalesce(current_offset(), <fallback>) — For incremental ingestion. On the first run, uses the fallback expression. On subsequent runs, uses the last ingested cursor value automatically tracked by the pipeline. The fallback can be any of the other supported primitives.

Rules:

Rule Detail
Curly braces required Every parameter value must be wrapped in { and }
Date format Must be YYYY-MM-DD. No other formats are supported.
Only subtraction + is not supported. Only - INTERVAL N DAY.
Only DAY unit WEEK, MONTH, YEAR, and HOUR are not supported.
Positive integers only INTERVAL -1 DAY is invalid. Use INTERVAL 1 DAY.
One coalesce per URL You can use at most one coalesce() expression per report URL. Using more than one causes an error.
No nested functions coalesce(current_offset(), coalesce(...)) is not valid.
current_offset() only inside coalesce current_offset() cannot be used standalone or in INTERVAL arithmetic.
Whitespace Leading/trailing spaces around the expression are fine. Spaces inside function names are not valid.
Parameter names Must match the exact prompt names configured in your Workday custom report.

Note

Use coalesce(current_offset(), <fallback>) only in the start prompt (for example, Date_Start), not in the end prompt. If you use coalesce in the end prompt, the end boundary is fixed after the first run and the pipeline re-fetches the same data range on every update.

The end prompt should always be deterministic and forward-moving: use current_date(), current_date() - INTERVAL N DAY, or a fixed date("YYYY-MM-DD").

Additional resources