PR #11 includes the following update:
- Updated default column macros to remove columns not used in their associated staging models. This prevents conflicts when bringing in this columns via the passthrough functionality.
PR #9 includes the following update:
- Updated model configuration in
dbt_project.yml
to correctly reflect project configuration name aszuora_source
. This is a breaking change because customers may unexpectedly see errors if they changed their materialization settings on any of their models.
- Updated seed files in
integration_tests
to match those indbt_zuora
for thev0.2.0
release.
PR #6 includes the following updates:
- Included a where clause within all staging models to filter out
_fivetran_deleted
records. - Added a conditional config within the
src_zuora.yml
to properly handle theorder
(reserved word) source table when using Snowflake as a destination.
- Added a call out in the identifier configuration section of the README to provide instructions for Snowflake users to handle the
order
source table if their destination has case sensitivity enabled.
- Added the
_fivetran_deleted
field to allget_*_columns
macros to ensure the field may be leveraged in the respective staging models.
- Included model disable logic within the
stg_zuora__credit_balance_adjustment_tmp
andstg_zuora__refund_invoice_payment_tmp
models in order to ensure they are not run if the appropriate variables are set tofalse
.
- Adjustment within the README to classify the package is no longer in development post v0.1.0 release.
- Updated
run_models.sh
script that is utilized in the integration tests of this package to ensure rollouts are successful prior to release. - Updated the pull request templates.
🎉 Initial Release 🎉
- This is the initial release of this package.
This package is designed to enrich your Fivetran Zuora data by doing the following:
- Cleans, tests, and prepares your Zuora data from Fivetran's connector for analysis.
- 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 leverage data in the format described here, which can then be used simultaneously with our Zuora modeling transformation package.
- Currently the package supports Postgres, Redshift, BigQuery, Databricks, and Snowflake. Additionally, this package is designed to work with dbt versions [">=1.3.0", "<2.0.0"].
For more information refer to the README.