LinkedIn Ad Analytics (docs)
This package models LinkedIn Ad Analytics 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.
The LinkedIn Ad Analytics dbt package is compatible with BigQuery, Redshift, and Snowflake.
This package contains transformation models, designed to work simultaneously with our LinkedIn Ad Analytics 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 |
---|---|
linkedin__ad_adapter | Each record represents the daily ad performance of each creative, including information about the used UTM parameters. |
linkedin__account_ad_report | Each record represents the daily ad performance of each account. |
linkedin__campaign_ad_report | Each record represents the daily ad performance of each campaign. |
linkedin__campaign_group_ad_report | Each record represents the daily ad performance of each campaign group. |
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 LinkedIn Ad Analytics data in the linkedin_ads
schema of your target database. If this is not where your LinkedIn Ad Analytics data is, please add the following configuration to your dbt_project.yml
file:
# dbt_project.yml
...
config-version: 2
vars:
linkedin_schema: your_database_name
linkedin_database: your_schema_name
For additional configurations for the source models, please visit the LinkedIn Ad Analytics 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.
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