Iterable

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

This package enables you to understand the efficacy of your growth marketing and customer engagement campaigns across email, SMS, push notification, and in-app platforms. The package achieves this by:

• Enriching the core EVENT table with data regarding associated users, campaigns, and channels.
• Creating current-state models of campaigns and users, enriched with aggregated event and interaction metrics.
• Creating a current-state model of message types and channels that each user is currently unsubscribed from.
• Re-creating the LIST_USER_HISTORY table. The table can be disabled from connector syncs but is required to connect users and their lists.

Modelslink

This package contains transformation models, designed to work simultaneously with our Iterable 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. Intermediate models are used to create these output models.

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/iterable
    version: [">=0.4.0", "<0.5.0"]

Check dbt Hub for the latest installation instructions, or read the dbt docs for more information on installing packages.

Configurationlink

By default, this package looks for your Iterable data in the iterable schema of your target database. If this is not where your Iterable data is, add the following configuration to your dbt_project.yml file:

...
config-version: 2

vars:
  iterable_database: your_database_name
  iterable_schema: your_schema_name 

Enabling and Disabling Modelslink

Your Iterable connector might not sync every table that this package expects. If your syncs exclude certain tables, it is because you either don’t use that functionality in Iterable or have actively excluded some tables from your syncs. In order to enable or disable the relevant functionality in the package, you will need to add the relevant variables.

By default, all variables are assumed to be true (with exception of iterable__using_user_device_history, which is set to false). You only need to add variables for the tables you would like to enable or disable respectively:

config-version: 2

vars:
    iterable__using_campaign_label_history: false                    # default is true
    iterable__using_user_unsubscribed_message_type_history: false    # default is true

    iterable__using_user_device_history: true                        # default is FALSE

Deprecated CAMPAIGN_SUPRESSION_LIST_HISTORY tablelink

The Iterable connector schema originally misspelled the CAMPAIGN_SUPPRESSION_LIST_HISTORY table as CAMPAIGN_SUPRESSION_LIST_HISTORY (note the singular P). As of August 2021, Fivetran has deprecated the misspelled table and will only continue syncing the correctly named CAMPAIGN_SUPPRESSION_LIST_HISTORY table.

By default, this package refers to the new table (CAMPAIGN_SUPPRESSION_LIST_HISTORY). To change this so that the package works with the old misspelled source table (we do not recommend this, however), add the following configuration to your dbt_project.yml file:

config-version: 2

vars:
    iterable_source:
        iterable__campaign_suppression_list_history_table: "campaign_supression_list_history"

Changing the Build Schemalink

By default, this package will build the following Iterable models within the schemas below in your target database:

• Final models within a schema titled (<target_schema> + _iterable)
• Intermediate models in (<target_schema> + _int_iterable)
• Staging models within a schema titled (<target_schema> + _stg_iterable)

If this is not where you would like your modeled Iterable data to be written to, add the following configuration to your dbt_project.yml file:

...
models:
  iterable:
    +schema: my_new_schema_name # leave blank for just the target_schema
    intermediate:
      +schema: my_new_schema_name # leave blank for just the target_schema
  iterable_source:
    +schema: my_new_schema_name # leave blank for just the target_schema

Note: If your profile does not have permissions to create schemas in your destination, you can set each +schema to blank. The package will then write all tables to your pre-existing target schema.

Contributionslink

Additional contributions to this package are very welcome! Please create issues or open PRs against main. See the Discourse post on the best workflow for contributing to a package.

Database Supportlink

This package has been tested on BigQuery, Snowflake, Redshift, and Postgres.

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