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, designed to work simultaneously with our Facebook 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.
|facebook_ads__ad_adapter||Each record represents the daily ad performance of each creative, including information about the used UTM parameters.|
|facebook_ads__account_report||Each record represents the daily ad performance of each account.|
|facebook_ads__campaign_report||Each record represents the daily ad performance of each campaign.|
|facebook_ads__ad_set_report||Each record represents the daily ad performance of each ad set.|
Include in your
packages: - package: fivetran/facebook_ads version: [">=0.4.0", "<0.5.0"]
To use this package, you will need to configure your Facebook Ads connector to pull the
BASIC_AD pre-built report. Follow the below steps in the Fivetran UI to do so:
- Navigate to the connector setup form (Setup -> Edit connection details for pre-existing connectors)
- Click Add table
- Select Pre-built Report
- Set the table name to
BASIC_ADas the corresponding pre-built report
- Select a daily aggregation period
- Click Ok and Save & test!
Source Data Locationlink
By default, this package will look for your Facebook Ads data in the
facebook_ads schema of your target database. If this is not where your Facebook Ads data is, please add the following configuration to your
... config-version: 2 vars: facebook_ads_schema: your_schema_name facebook_ads_database: your_database_name
For additional configurations for the source models, visit the Facebook Ads source package.
Changing the Build Schemalink
By default this package will build the Facebook Ads staging models within a schema titled (<target_schema> +
_stg_facebook_ads), the Facebook Creative History models within a schema titled (<target_schema> +
_facebook_ads_creative_history), and the final Facebook Ads models within a schema titled (<target_schema> +
_facebook_ads) in your target database. If this is not where you would like your modeled Facebook data to be written to, add the following configuration to your
... models: facebook_ads: +schema: my_new_schema_name # leave blank for just the target_schema facebook_ads_creative_history: +schema: my_new_schema_name # leave blank for just the target_schema facebook_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.
- Provide feedback on our existing dbt packages or what you’d like to see next
- Find all of Fivetran’s pre-built dbt packages in our dbt hub
- Learn more about Fivetran in the Fivetran docs
- Learn how to orchestrate your models with Fivetran Transformations for dbt Core™
- Check out Fivetran’s blog
- Learn more about dbt in the dbt docs
- Check out Discourse for commonly asked questions and answers
- Join the chat on Slack for live discussions and support
- Find dbt events near you
- Check out the dbt blog for the latest news on dbt’s development and best practices