This package models Facebook Ads data from Fivetran's connector. It uses data in the format described by this ERD.
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 package contains transformation models, designed to work simultaneously with our Facebook Ads source 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.
| model | description |
|---|---|
| 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. |
Check dbt Hub for the latest installation instructions, or read the dbt docs for more information on installing packages.
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 dbt_project.yml file:
# dbt_project.yml
...
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.
Additional contributions to this package are very welcome! Please create issues or open PRs against master. 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
- 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