Releases: fivetran/dbt_microsoft_ads
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 thedbt-labls/dbt_utils
package. If your project also utilizes a version of thefishtown-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.
Postgres Compatibility
🎉 Postgres Compatibility 🎉
This release incorporates Postgres compatibility changes. These changes are non-breaking and only include changes for integration testing and Postgres specific updates to the package.
Databricks Compatibility
This release incorporates the following non-breaking changes:
- Databricks compatibility
Custom Schema Update
🚨 This update introduces a breaking changes in the form of custom schemas to output models into a respective <target.schema>+_microsoft_ads
schema. Refer to the ReadMe for more details. 🚨
The release also:
- Incorporates Github pages for easy dbt docs hosting
- Minor documentation updates
dbt 0.19.0 Compatibility
This release introduces compatibility with dbt 0.19.0. There are no known breaking changes.
Initial Release
This is the initial release of this package.
The main focus of the package is to transform the core ad object tables into analytics-ready models, including an 'ad adapter' model that can be easily unioned in to other ad platform packages to get a single view.
Currently the package supports Redshift, BigQuery and Snowflake.