Workday HCM dbt Package
This dbt package transforms data from Fivetran's Workday HCM connector into analytics-ready tables.
Resources
- Number of materialized models¹: 29
- Connector documentation
- dbt package documentation
What does this dbt package do?
This package enables you to transform core object tables into analytics-ready models and gather daily historical records of employees. It creates enriched models with metrics focused on employee demographics, organizational structures, job profiles, and position management.
Output schema
Final output tables are generated in the following target schema:
<your_database>.<connector/schema_name>_workday
Final output tables
By default, this package materializes the following final tables:
| Table | Description |
|---|---|
| workday__employee_overview | Consolidates employee profiles with personal information, position details, employment status, demographics, compensation data, and tenure metrics to analyze workforce composition, retention, turnover, and compensation across the organization. Example Analytics Questions:
|
| workday__job_overview | Provides comprehensive job profiles with job family classifications, job titles, descriptions, and summaries to analyze job structures, recruitment patterns, and workforce planning needs. Example Analytics Questions:
|
| workday__organization_overview | Maps organizational hierarchies with organization codes, types, roles, associated positions and workers, plus manager and superior organization relationships to enable multi-dimensional analysis of organizational structure and headcount. Example Analytics Questions:
|
| workday__position_overview | Tracks position details including vacancy status, availability flags, worker assignments, job profiles, organizational ties, and compensation information to optimize hiring efforts, monitor position utilization, and control workforce costs. Example Analytics Questions:
|
| workday__employee_daily_history | Chronicles daily employee snapshots with position assignments, personal info, employment status, compensation details, and demographic data to enable historical analysis, track employee changes over time, and measure workforce metrics at any point in time. Example Analytics Questions:
|
| workday__monthly_summary | Summarizes monthly workforce metrics including new hires, attrition (voluntary and involuntary), active headcount, average compensation, and tenure to support strategic workforce planning and trend analysis. Example Analytics Questions:
|
| workday__worker_position_org_daily_history | Tracks daily worker-position-organization combinations from activation to present or termination to enable historical organizational analysis and connect workers to organizational hierarchies over time. Example Analytics Questions:
|
¹ Each Quickstart transformation job run materializes these models if all components of this data model are enabled. This count includes all staging, intermediate, and final models materialized as view, table, or incremental.
Prerequisites
To use this dbt package, you must have the following:
- At least one Fivetran Workday HCM connection syncing data into your destination.
- A BigQuery, Snowflake, Redshift, Databricks, or PostgreSQL destination.
How do I use the dbt package?
You can either add this dbt package in the Fivetran dashboard or import it into your dbt project:
- To add the package in the Fivetran dashboard, follow our Quickstart guide.
- To add the package to your dbt project, follow the setup instructions in the dbt package's README file to use this package.
How is this package maintained and can I contribute?
Package Maintenance
The Fivetran team maintaining this package only maintains the latest version of the package. We highly recommend you stay consistent with the latest version of the package and refer to the CHANGELOG and release notes for more information on changes across versions.
Contributions
A small team of analytics engineers at Fivetran develops these dbt packages. However, the packages are made better by community contributions.
We highly encourage and welcome contributions to this package. Learn how to contribute to a package in dbt's Contributing to an external dbt package article.