fivetran/dbt_workday

Fivetran's Workday HCM dbt package

Workday HCM dbt Package (Docs)

📣 What does this dbt package do?

This package models Workday HCM data from Fivetran's connector. It uses data in the format described by this ERD.

The main focus of the package is to transform the core object tables into analytics-ready models, including:

• Materializes Workday HCM staging tables which leverage data in the format described by this ERD. These staging tables clean, test, and prepare your Workday data from Fivetran's connector for analysis by doing the following:
• Name columns for consistency across all packages and for easier analysis
  • Primary keys are renamed from id to <table name>_id.
• Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
• Provides insight into your Workday HCM data across the following grains:
  • Employee, job, organization, position.
• Generates a comprehensive data dictionary of your Workday HCM data through the dbt docs site.

This package does not apply freshness tests to source data due to the variability of survey cadences.

The following table provides a detailed list of all models materialized within this package by default.

TIP: See more details about these models in the package's dbt docs site.

model	description
workday__employee_overview	Each record represents an employee with enriched personal information and the positions they hold. This helps measure employee demographic and geographical distribution, overall retention and turnover, and compensation analysis of their employees.
workday__job_overview	Each record represents a job with enriched details on job profiles and job families. This allows users to understand recruitment patterns and details within a job and job groupings.
workday__organization_overview	Each record represents organization, organization roles, as well as positions and workers tied to these organizations. This allows end users to slice organizational data at any grain to better analyze organizational structures.
workday__position_overview	Each record represents a position with enriched data on positions. This allows end users to understand position availabilities, vacancies, cost to optimize hiring efforts.

🎯 How do I use the dbt package?

Step 1: Prerequisites

To use this dbt package, you must have the following:

• At least one Fivetran Workday HCM connector syncing data into your destination.
• A BigQuery, Snowflake, Redshift, Databricks, or PostgreSQL destination.

Databricks dispatch configuration

If you are using a Databricks destination with this package, you must add the following (or a variation of the following) dispatch configuration within your dbt_project.yml. This is required in order for the package to accurately search for macros within the dbt-labs/spark_utils then the dbt-labs/dbt_utils packages respectively.

dispatch:
  - macro_namespace: dbt_utils
    search_order: ['spark_utils', 'dbt_utils']

Step 2: Install the package

Include the following Workday package version in your packages.yml file:

TIP: Check dbt Hub for the latest installation instructions or read the dbt docs for more information on installing packages.

packages:
  - package: fivetran/workday
    version: [">=0.1.0", "<0.2.0"] # we recommend using ranges to capture non-breaking changes automatically

Step 3: Define database and schema variables

Single connector

By default, this package runs using your destination and the workday schema. If this is not where your Workday HCM data is (for example, if your Workday HCM schema is named workday_fivetran), add the following configuration to your root dbt_project.yml file:

# dbt_project.yml

vars:
    workday_database: your_database_name
    workday_schema: your_schema_name

Union multiple connectors

If you have multiple Workday HCM connectors in Fivetran and would like to use this package on all of them simultaneously, we have provided functionality to do so. The package will union all of the data together and pass the unioned table into the transformations. You will be able to see which source it came from in the source_relation column of each model. To use this functionality, you will need to set either the workday_union_schemas OR workday_union_databases variables (cannot do both) in your root dbt_project.yml file:

# dbt_project.yml

vars:
    workday_union_schemas: ['workday_usa','workday_canada'] # use this if the data is in different schemas/datasets of the same database/project
    workday_union_databases: ['workday_usa','workday_canada'] # use this if the data is in different databases/projects but uses the same schema name

Please be aware that the native source.yml connection set up in the package will not function when the union schema/database feature is utilized. Although the data will be correctly combined, you will not observe the sources linked to the package models in the Directed Acyclic Graph (DAG). This happens because the package includes only one defined source.yml.

To connect your multiple schema/database sources to the package models, follow the steps outlined in the Union Data Defined Sources Configuration section of the Fivetran Utils documentation for the union_data macro. This will ensure a proper configuration and correct visualization of connections in the DAG.

(Optional) Step 4: Additional configurations

Changing the Build Schema

By default this package will build the Workday HCM staging models within a schema titled (<target_schema> + _stg_workday) and the Workday HCM final models within a schema titled (<target_schema> + _workday) in your target database. If this is not where you would like your modeled Workday HCM data to be written to, add the following configuration to your dbt_project.yml file:

# dbt_project.yml

models:
  workday:
    +schema: my_new_schema_name # leave blank for just the target_schema
    staging:
        +schema: my_new_schema_name # leave blank for just the target_schema

Change the source table references

If an individual source table has a different name than the package expects, add the table name as it appears in your destination to the respective variable:

IMPORTANT: See this project's dbt_project.yml variable declarations to see the expected names.

# dbt_project.yml

vars:
    workday_<default_source_table_name>_identifier: your_table_name 

(Optional) Step 5: Orchestrate your models with Fivetran Transformations for dbt Core™

Expand for details

Fivetran offers the ability for you to orchestrate your dbt project through Fivetran Transformations for dbt Core™. Learn how to set up your project for orchestration through Fivetran in our Transformations for dbt Core setup guides.

🔍 Does this package have dependencies?

This dbt package is dependent on the following dbt packages. Please be aware that these dependencies are installed by default within this package. For more information on the following packages, refer to the dbt hub site.

IMPORTANT: If you have any of these dependent packages in your own packages.yml file, we highly recommend that you remove them from your root packages.yml to avoid package version conflicts.

packages:
    - package: fivetran/fivetran_utils
      version: [">=0.4.0", "<0.5.0"]

    - package: dbt-labs/dbt_utils
      version: [">=1.0.0", "<2.0.0"]

🙌 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. Check out this dbt Discourse article on the best workflow for contributing to a package!

🏪 Are there any resources available?

• If you have questions or want to reach out for help, please refer to the GitHub Issue section to find the right avenue of support for you.
• If you would like to provide feedback to the dbt package team at Fivetran or would like to request a new dbt package, fill out our Feedback Form.
• Have questions or want to be part of the community discourse? Create a post in the Fivetran community and our team along with the community can join in on the discussion!

dbt_workday's Issues

[Bug] _fivetran_active can pull future dated records from `worker_history` rather than the currently active one

Is there an existing issue for this?

• I have searched the existing issues

Describe the issue

Currently our dbt_workday models are filtering on the _fivetran_active record to grab a live look at employee status, current positions, etc. However, there are cases where this is not the case in the new worker_history model.

Examples:

• A worker is given a compensation change, effective in X months. This will reflect that record and not their current active compensation.
• A worker is given a promotion, effective in Y months. This will reflect that record and not their current worker status.

These cases were validated with @fivetran-tommy internally.

The best way to fix this issue for most cases is to filter on the _fivetran_start and _fivetran_end dates and look at which of these records falls within the current timestamp.

Relevant error log or model output

No response

Expected behavior

The end models should produce the records that are active as of the current moment.

dbt Project configurations

default

Package versions

packages:

• package: fivetran/workday
  version: [">=0.1.0", "<0.2.0"]

What database are you using dbt with?

bigquery

dbt Version

dbt v1.7.4

Additional Context

No response

Are you willing to open a PR to help address this issue?

• Yes.
• Yes, but I will need assistance and will schedule time during our office hours for guidance
• No.