v0.7.0 dbt_lever

PR #21 includes the following updates:

Features

• For Fivetran Lever connectors created on or after July 27, 2024, the USER and INTERVIEWER_USER source tables have been renamed to USERS and INTERVIEW_USER, respectively. This package now prioritizes the USERS and INTERVIEW_USER tables if available, falling back to USER and INTERVIEWER_USER if not.
  • If you have both tables in your schema and would like to specify this package to leverage the USER and/or INTERVIEWER_USER tables, you can set the variables lever__using_users and/or lever__using_interview_user to false in your dbt_project.yml.
  • For more information, refer to the July 2024 connector release notes and the related README section.
• Introduced the ability to union source data from multiple Lever connectors. For more details, see the related README section.
• Streamlined testing by removing tests from intermediate models and consolidating them in the end models, optimizing resource usage and prioritizing the final outputs.

Bug fixes

• Fixed an issue where the dbt package would error due to a missing CONTACT_LINK source table for users without source data, even though it was enabled in the Fivetran Connector. A null-filled table will now be generated in such cases.

Documentation updates

• Add missing field definitions to dbt docs.

Under the hood

• In the source package, updated temporary models to union source data using the fivetran_utils.union_data macro.
• Added the source_relation column in each staging model to identify the origin of each field, utilizing the fivetran_utils.source_relation macro.
• Updated tests to include the new source_relation column.
• Included the source_relation column in all joins and window function partition clauses in the transform package.
• Added consistency tests for end models.
• Turned off freshness tests for the USER/USERS and INTERVIEW_USER/INTERVIEWER_USER sources to avoid possible conflicts.

Full Changelog: v0.6.0...v0.7.0

v0.6.0 dbt_lever

This release of dbt_lever includes:

🎉 Feature Update 🎉

• PostgreSQL and Databricks compatibility! (#18)

🚘 Under the Hood 🚘

• Incorporated the new fivetran_utils.drop_schemas_automation macro into the end of each Buildkite integration test job. (#16)
• Updated the pull request templates. (#16)

Full Changelog: v0.5.0...v0.6.0

dbt_lever v0.5.0

🚨 Breaking Changes 🚨:

PR #14 includes the following breaking changes:

• Dispatch update for dbt-utils to dbt-core cross-db macros migration. Specifically {{ dbt_utils.<macro> }} have been updated to {{ dbt.<macro> }} for the below macros:
  • any_value
  • bool_or
  • cast_bool_to_text
  • concat
  • date_trunc
  • dateadd
  • datediff
  • escape_single_quotes
  • except
  • hash
  • intersect
  • last_day
  • length
  • listagg
  • position
  • replace
  • right
  • safe_cast
  • split_part
  • string_literal
  • type_bigint
  • type_float
  • type_int
  • type_numeric
  • type_string
  • type_timestamp
  • array_append
  • array_concat
  • array_construct
• For current_timestamp and current_timestamp_in_utc macros, the dispatch AND the macro names have been updated to the below, respectively:
  • dbt.current_timestamp_backcompat
  • dbt.current_timestamp_in_utc_backcompat
• Dependencies on fivetran/fivetran_utils have been upgraded, previously [">=0.3.0", "<0.4.0"] now [">=0.4.0", "<0.5.0"].

dbt_lever v0.4.0

Happy Thursday! 🍰

This release of the dbt_lever package includes the following updates:

🎉 Documentation and Feature Updates

• Updated README documentation updates for easier navigation and setup of the dbt package. (#13)
• Included lever_[source_table_name]_identifier variable within the Lever source package for additional flexibility within the package when source tables are named differently. (#13)

lever 0.3.0

🎉 dbt v1.0.0 Compatibility 🎉

🚨 Breaking Changes 🚨

• Adjusts the require-dbt-version to now be within the range [">=1.0.0", "<2.0.0"]. Additionally, the package has been updated for dbt v1.0.0 compatibility. If you are using a dbt version <1.0.0, you will need to upgrade in order to leverage the latest version of the package.
  • For help upgrading your package, I recommend reviewing this GitHub repo's Release Notes on what changes have been implemented since your last upgrade.
  • For help upgrading your dbt project to dbt v1.0.0, I recommend reviewing dbt-labs upgrading to 1.0.0 docs for more details on what changes must be made.
• Upgrades the package dependency to refer to the latest dbt_lever_source. Additionally, the latest dbt_lever_source package has a dependency on the latest dbt_fivetran_utils. Further, the latest dbt_fivetran_utils package also has a dependency on dbt_utils [">=0.8.0", "<0.9.0"].
  • Please note, if you are installing a version of dbt_utils in your packages.yml that is not in the range above then you will encounter a package dependency error.

dbt 0.20.0 Compatibility

🎉 dbt 0.20.0 Compatibility 🎉

🚨 This is a breaking change! 🚨 dbt v0.20.0 or greater is required for this release. If you are not ready to upgrade, consider using a previous release of this package.

Additional considerations when upgrading to this package:

• This package utilizes the latest v0.7.x release of the dbt-labls/dbt_utils package. If your project also utilizes a version of the fishtown-analytics/dbt_utils package then you will receive a duplicate package error. If this is the case you will need to consider upgrading your other packages to be compatible with this update or use a previous release of this package.
• Similar to the above point, all previous Fivetran dbt packages utilize the fishtown-analytics/dbt_utils package and you will need to upgrade all Fivetran dbt packages to the latest dbt 0.20.0 compatibility releases in order for your packages to run without package conflicts.

Package Upgrades

This new release allows you to disable all models and logic related to the posting_tag table using the lever_using_posting_tag variable.

Many thanks to @nelsonauner for working on this. 😄

Initial Release

This is the initial release of this package.

This package enables you to better understand recruiting, hiring, and interviewing practices at your company.

Currently the package supports Redshift, BigQuery, and Snowflake.