This package models Twitter 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 is especially easy using our Ad Reporting package.
Modelslink
This package contains transformation models, designed to work simultaneously with our Twitter 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.
model | description |
---|---|
twitter__ad_adapter | Each record represents the daily ad performance of each creative, including information about the used UTM parameters. |
twitter__line_item_report | Each record represents the daily ad performance of each line item. |
twitter__campaign_report | Each record represents the daily ad performance of each campaign. |
Installation Instructionslink
Check dbt Hub for the latest installation instructions, or read the dbt docs for more information on installing packages.
Include in your packages.yml
packages:
- package: fivetran/twitter_ads
version: [">=0.4.0", "<0.5.0"]
Configurationlink
By default, this package will look for your Twitter Ads data in the twitter_ads
schema of your target database. If this is not where your Twitter Ads data is, please add the following configuration to your dbt_project.yml
file:
...
config-version: 2
vars:
twitter_ads_schema: your_schema_name
twitter_ads_database: your_database_name
For additional configurations for the source models, visit the Twitter Ads source package.
Changing the Build Schemalink
By default this package will build the Twitter Ads staging models within a schema titled (<target_schema> + _stg_twitter_ads
) and the Twitter Ads final models with a schema titled (<target_schema> + _twitter_ads
) in your target database. If this is not where you would like your modeled Twitter Ads data to be written to, add the following configuration to your dbt_project.yml
file:
...
models:
twitter_ads:
+schema: my_new_schema_name # leave blank for just the target_schema
twitter_ads_source:
+schema: my_new_schema_name # leave blank for just the target_schema
Database Supportlink
This package has been tested on BigQuery, Snowflake, Redshift, Postgres, and Databricks.
Databricks Dispatch Configurationlink
dbt 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']
Contributionslink
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.
Resources:link
- Provide feedback on our existing dbt packages or what you’d like to see next
- Have questions, feedback, or need help? Book a time during our office hours using Calendly or email us at solutions@fivetran.com
- Find all of Fivetran’s pre-built dbt packages in our dbt hub
- Learn how to orchestrate your models with Fivetran Transformations for dbt Core™
- Learn more about Fivetran overall in our 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