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 v0.7.0 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.

Fivetran Utils Dependency Update

🚧 Fivetran Utils Dependency Update 🚧

This release includes the following non-breaking changes:

• Update to the packages.yml to reference the recently released Fivetran Utils package. This is a necessary update to ensure this package is compatible with previous dbt releases before dbt v0.20.0 updates take place.

Minor: Remove Order By Clause

This release introduces the removal of an unnecessary ORDER BY clause in the stg_zendesk__ticket_field_history model which was causing a resources exceeded error in BigQuery

Custom Schema for Staging Tables

🚨 This update introduces a breaking change: Output models will now be written to (<target_schema> + _zendesk_staging) 🚨

No other changes were applied to this release.

Package Updates

🚨 This update introduces a breaking change: Output models are renamed to include a double underscore between the source name and the table name. For example, stg_zendesk_ticket is now stg_zendesk__ticket

The release also:

• Introduces CircleCI testing
• Introduces user_tag, brand, ticket_form_history, domain_name, and organization_tag staging models. Additionally, user_tag, ticket_form_history, domain_name, and organization_tag variables are included to disable the models if the tables are not used.
• Utilizes our fill_staging_columns macro for the creation of staging tables. If you do not have a required column necessary for this package, the fill_staging_column will produce this column (filled with nulls) and prevent the error

Bug Fix

In Snowflake, v0.1.0 fails due to the use of the "Group" keyword. This update introduces a fix for that!

Initial Release

This is the initial release of this package.

This package is designed enrich your Fivetran data by doing the following:

• Add descriptions to tables and columns that are synced using Fivetran
• Add freshness tests to source data
• Add column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
• Model staging tables, which will be used in our transform package

Currently the package supports Redshift, BigQuery and Snowflake.