Snapchat Ads (Source)

This package models Snapchat Ads data from Fivetran’s connector. It uses data in the format described by this ERD.

Modelslink

This package contains staging models, designed to work simultaneously with our Snapchat Ads transform package and our multi-platform Ad Reporting package. The staging models name columns consistently across all packages:

• Boolean fields are prefixed with is_ or has_
• Timestamps are appended with _timestamp
• ID primary keys are prefixed with the name of the table. For example, the campaign table’s ID column is renamed campaign_id.

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/snapchat_ads_source
    version: [">=0.3.0", "<0.4.0"]

Configurationlink

By default, this package will look for your Snapchat Ads data in the snapchat_ads schema of your target database. If this is not where your Snapchat Ads data is, please add the following configuration to your dbt_project.yml file:

...
config-version: 2

vars:
    snapchat_schema: your_schema_name
    snapchat_database: your_database_name 

Changing the Build Schemalink

By default, this package will build the Snapchat Ads staging models within a schema titled (<target_schema> + _stg_snapchat_ads) in your target database. If this is not where you would like your Snapchat Ads staging data to be written to, add the following configuration to your dbt_project.yml file:

...
models:
    snapchat_ads_source:
      +schema: my_new_schema_name # leave blank for just the target_schema

Contributionslink

Don’t see a model or specific metric you would have liked to be included? Notice any bugs when installing and running the package? If so, we highly encourage and welcome contributions to this package! Please create issues or open PRs against master. See the Discourse post for information on how to contribute to a package.

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']

Resources:link

• Provide feedback on our existing dbt packages or what you’d like to see next
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• 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
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