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. This is especially easy using our Ad Reporting package.
This package contains transformation models that are designed to work simultaneously with our Microsoft Advertising 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.
|microsoft_ads__ad_adapter||Each record represents the daily ad performance of each ad, including information about the used UTM parameters.|
|microsoft_ads__account_report||Each record represents the daily ad performance of each account.|
|microsoft_ads__ad_group_report||Each record represents the daily ad performance of each ad group.|
|microsoft_ads__campaign_report||Each record represents the daily ad performance of each campaign.|
Include in your
packages: - package: fivetran/microsoft_ads version: [">=0.4.0", "<0.5.0"]
By default, this package looks for your Microsoft Advertising data in the
microsoft_ads schema of your target database. If this is not where your Microsoft Advertising data is, add the following configuration to your
... config-version: 2 vars: microsoft_ads_schema: your_schema_name microsoft_ads_database: your_database_name
For additional configurations for the source models, visit the Microsoft Advertising source package.
UTM Auto Tagging Featurelink
This package assumes you are manually adding UTM tags to the
final_url field within the
ad_history table. If you are leveraging the auto-tag feature within Microsoft Ads then you will want to enable the
microsoft_auto_tagging_enabled variable to correctly populate the UTM fields within the
vars: microsoft_auto_tagging_enabled: true # False by default
Changing the Build Schemalink
By default this package will build the Microsoft Ads staging models within a schema titled (<target_schema> +
_stg_microsoft_ads) and the Microsoft Ads final models with a schema titled (<target_schema> +
_microsoft_ads) in your target database. If this is not where you would like your modeled Microsoft Ads data to be written to, add the following configuration to your
... models: microsoft_ads: +schema: my_new_schema_name # leave blank for just the target_schema microsoft_ads_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 this post on the best workflow for contributing to a package.
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