Intercom (Source)

NOTE: Our Intercom model and source dbt packages only work with connectors that were created in July 2020 or later. If you created your connector before July 2020, you must set up a new Intercom connector to use these dbt packages.

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

This package enriches your Fivetran data by doing the following:

• Adds descriptions to tables and columns that are synced using Fivetran
• Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
• Models staging tables, which will be used in our transform package

Modelslink

This package contains staging models, designed to work simultaneously with our Intercom transform package. The staging models name columns consistently across all packages:

• Boolean fields are prefixed with is_ or has_
• Timestamps are appended with _at
• ID primary keys are prefixed with the name of the table. For example, the admin table’s ID column is renamed admin_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/intercom_source
    version: [">=0.5.0", "<0.6.0"]

Configurationlink

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

...
config-version: 2

vars:
    intercom_database: your_database_name
    intercom_schema: your_schema_name

This package includes all source columns defined in the macros folder. If you want to include custom fields in this package, you can add more columns using our pass-through column variables.

...
vars:
  intercom__company_history_pass_through_columns: [company_custom_field_1, company_custom_field_2]
  intercom__contact_history_pass_through_columns: [super_cool_contact_field]

Additionally, this package includes Intercom’s company tag, contact tag, contact company,conversation tag, team and team admin mapping tables. If you do not use these tables, add the configuration below to your dbt_project.yml. By default, these variables are set to True:

...
vars:
  intercom__using_contact_company: False
  intercom__using_company_tags: False
  intercom__using_contact_tags: False
  intercom__using_conversation_tags: False
  intercom__using_team: False

Changing the Build Schemalink

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

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

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.

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
• Find all of Fivetran’s pre-built dbt packages in our dbt hub
• Learn more about Fivetran in the Fivetran docs
• Learn how to orchestrate your models with Fivetran Transformations for dbt Core™
• 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