Snapchat Ads Source dbt Package (Docs)

Union multiple connectors

If you have multiple snapchat_ads connectors in Fivetran and would like to use this package on all of them simultaneously, we have provided functionality to do so. The package will union all of the data together and pass the unioned table into the transformations. You will be able to see which source it came from in the source_relation column of each model. To use this functionality, you will need to set either the snapchat_ads_union_schemas OR snapchat_ads_union_databases variables (cannot do both) in your root dbt_project.yml file:

vars:
    snapchat_ads_union_schemas: ['snapchat_ads_usa','snapchat_ads_canada'] # use this if the data is in different schemas/datasets of the same database/project
    snapchat_ads_union_databases: ['snapchat_ads_usa','snapchat_ads_canada'] # use this if the data is in different databases/projects but uses the same schema name

NOTE: The native source.yml connection set up in the package will not function when the union schema/database feature is utilized. Although the data will be correctly combined, you will not observe the sources linked to the package models in the Directed Acyclic Graph (DAG). This happens because the package includes only one defined source.yml.

To connect your multiple schema/database sources to the package models, follow the steps outlined in the Union Data Defined Sources Configuration section of the Fivetran Utils documentation for the union_data macro. This will ensure a proper configuration and correct visualization of connections in the DAG.

Passing Through Additional Metrics

By default, this package will select swipes, impressions, spend, conversion_purchases_value, and conversion_purchases (or whichever fields are specified by the snapchat_ads__conversion_fields variable in the next section) from the source reporting tables to store into the staging models. If you would like to pass through additional metrics to the staging models, add the below configurations to your dbt_project.yml file. These variables allow for the pass-through fields to be aliased (alias) if desired, but not required. Use the below format for declaring the respective pass-through variables:

vars:
    snapchat_ads__ad_hourly_passthrough_metrics: 
      - name: "new_custom_field"
        alias: "custom_field_alias"
        transform_sql: "coalesce(custom_field_alias, 0)" # reference the `alias` here if you are using one
      - name: "unique_int_field"
        alias: "field_id"
      - name: "another_one"
        transform_sql: "coalesce(another_one, 0)" # reference the `name` here if you're not using an alias
    snapchat_ads__ad_squad_hourly_passthrough_metrics:
      - name: "this_field"
    snapchat_ads__campaign_hourly_report_passthrough_metrics:
      - name: "unique_string_field"
        alias: "field_id"

Note: Make sure to exercise due diligence when adding metrics to these models. The metrics added by default (swipes, impressions, spend, and conversions) have been vetted by the Fivetran team, maintaining this package for accuracy. There are metrics included within the source reports, such as metric averages, which may be inaccurately represented at the grain for reports created in this package. You must ensure that whichever metrics you pass through are appropriate to aggregate at the respective reporting levels in this package.

Important: You do NOT need to add conversions in this way. See the following section for an alternative implementation.

Configuring Conversion Fields

Separate from the above passthrough metrics, the package will also include conversion metrics based on the snapchat_ads__conversion_fields variable, in addition to the conversion_purchases_value field.

By default, the data models consider conversion_purchases to be conversions. These should cover most use cases, but, say, if you would like to consider adding payment info, adding to wishlist, adding to the cart, etc. to also be conversions, you would apply the following configuration with the original source names of the conversion fields (not aliases you provided in the section above):

# dbt_project.yml
vars:
    snapchat_ads__conversion_fields: ['conversion_purchases', 'conversion_add_billing', 'conversion_save', 'conversion_add_cart']

We introduced support for conversion fields in our *_hourly_report data models in the v0.7.0 release of the package, but customers might have been bringing in these conversion fields earlier using the passthrough fields variables. The data models will avoid "duplicate column" errors automatically if this is the case.

Change the source table references

If an individual source table has a different name than the package expects, add the table name as it appears in your destination to the respective variable. This is not available when running the package on multiple unioned connectors.

IMPORTANT: See this project's dbt_project.yml variable declarations to see the expected names.

vars:
    snapchat_ads_<default_source_table_name>_identifier: your_table_name 

Change the build schema

By default, this package builds the Snapchat Ads staging models (9 views, 9 tables) within a schema titled (<target_schema> + _stg_snapchat_ads) in your destination. If this is not where you would like your Snapchat Ads staging data to be written to, add the following configuration to your root dbt_project.yml file:

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

Fivetran offers the ability for you to orchestrate your dbt project through Fivetran Transformations for dbt Core™. Learn how to set up your project for orchestration through Fivetran in our Transformations for dbt Core™ setup guides.