This package transforms 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. This is especially easy using our Ad Reporting package.
The Pinterest Ads dbt package is compatible with BigQuery, Redshift, and Snowflake.
This package contains transformation models, designed to work simultaneously with our Pinterest Ads source package and our multi-platform Ad Reporting package. A dependency on the source package is declared in this package’s
packages.yml file, so it will automatically download when you run
dbt deps. The primary outputs of this package are described below.
|pinterest_ads__ad_adapter||Each record represents the daily ad performance of each pin promotion, including information about its UTM parameters.|
|pinterest_ads__ad_group_ad_report||Each record represents the daily ad performance of each add group.|
|pinterest_ads__campaign_ad_report||Each record represents the daily ad performance of each campaign.|
Include in your
packages: - package: fivetran/pinterest version: [">=0.5.0", "<0.6.0"]
By default, this package will look for your Pinterest Ads data in the
pinterest_ads schema of your target database. If this is not where your Pinterest Ads data is, add the following configuration to your
... config-version: 2 vars: pinterest_database: your_database_name pinterest_schema: your_schema_name
For additional source model configurations, see our Pinterest Ads source package.
This package allows for custom columns not defined within the
stg_pinterest_ads__pin_promotion_report model to be passed through to the final models within this package. These custom columns may be applied using the
pin_promotion_report_pass_through_metric variable. To apply custom passthrough columns use the below format:
... vars: pin_promotion_report_pass_through_metric: - 'cool_new_field' - 'my_other_column' - 'pass_this_through_too'
Changing the Build Schemalink
By default this package will build the Pinterest Ads staging models within a schema titled (<target_schema> +
_stg_pinterest) and the Pinterest Ads final models with a schema titled (<target_schema> +
_pinterest) in your target database. If this is not where you would like your modeled Pinterest Ads data to be written to, add the following configuration to your
... models: pinterest: +schema: my_new_schema_name # leave blank for just the target_schema pinterest_source: +schema: my_new_schema_name # leave blank for just the target_schema
This package has been tested on BigQuery, Snowflake, Redshift, Postgres, and Databricks.
Databricks Dispatch Configurationlink
v0.20.0 introduced a new project-level dispatch configuration that enables an “override” setting for all dispatched macros. If you are using a Databricks destination with this package you will need to add the below (or a variation of the below) 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']
Additional contributions to this package are very welcome! Please create issues
or open PRs against
main. Check out
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