• Materializes HubSpot staging tables which leverage data in the format described by this ERD. These staging tables clean, test, and prepare your HubSpot data from Fivetran's connector for analysis by doing the following:
  • Name columns for consistency across all packages and for easier analysis
  • Adds freshness tests to source data
  • Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
• Generates a comprehensive data dictionary of your HubSpot data through the dbt docs site.
• These tables are designed to work simultaneously with our HubSpot transformation package.

To use this dbt package, you must have the following:

• At least one Fivetran HubSpot connector syncing data into your destination.
• A BigQuery, Snowflake, Redshift, PostgreSQL, or Databricks destination.

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']

Include the following hubspot_source package version in your packages.yml file.

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

packages:
  - package: fivetran/hubspot_source
    version: [">=0.7.0", "<0.8.0"]

By default, this package runs using your destination and the hubspot schema. If this is not where your HubSpot data is (for example, if your HubSpot schema is named hubspot_fivetran), add the following configuration to your root dbt_project.yml file:

vars:
    hubspot_database: your_destination_name
    hubspot_schema: your_schema_name 

When setting up your Hubspot connection in Fivetran, it is possible that not every table this package expects will be synced. This can occur because you either don't use that functionality in Hubspot or have actively decided to not sync some tables. Therefore we have added enable/disable configs in the src.yml to allow you to disable certain sources not present. Downstream models are automatically disabled as well. In order to disable the relevant functionality in the package, you will need to add the relevant variables in your root dbt_project.yml. By default, all variables are assumed to be true (with exception of hubspot_service_enabled, hubspot_ticket_deal_enabled, and hubspot_contact_merge_audit_enabled). You only need to add variables for the tables different from default:

# dbt_project.yml
vars:
  # Marketing

  hubspot_marketing_enabled: false                        # Disables all marketing models
  hubspot_contact_enabled: false                          # Disables the contact models
  hubspot_contact_list_enabled: false                     # Disables contact list models
  hubspot_contact_list_member_enabled: false              # Disables contact list member models
  hubspot_contact_property_enabled: false                 # Disables the contact property models
  hubspot_email_event_enabled: false                      # Disables all email_event models and functionality
  hubspot_email_event_bounce_enabled: false
  hubspot_email_event_click_enabled: false
  hubspot_email_event_deferred_enabled: false
  hubspot_email_event_delivered_enabled: false
  hubspot_email_event_dropped_enabled: false
  hubspot_email_event_forward_enabled: false
  hubspot_email_event_click_enabled: false
  hubspot_email_event_open_enabled: false
  hubspot_email_event_print_enabled: false
  hubspot_email_event_sent_enabled: false
  hubspot_email_event_spam_report_enabled: false
  hubspot_email_event_status_change_enabled: false
  
  hubspot_contact_merge_audit_enabled: true               # Enables contact merge auditing to be applied to final models (removes any merged contacts that are still persisting in the contact table)

  # Sales

  hubspot_sales_enabled: false                            # Disables all sales models
  hubspot_company_enabled: false
  hubspot_deal_enabled: false
  hubspot_deal_company_enabled: false
  hubspot_deal_contact_enabled: false
  hubspot_engagement_enabled: false                       # Disables all engagement models and functionality
  hubspot_engagement_contact_enabled: false
  hubspot_engagement_company_enabled: false
  hubspot_engagement_deal_enabled: false
  hubspot_engagement_call_enabled: false
  hubspot_engagement_email_enabled: false
  hubspot_engagement_meeting_enabled: false
  hubspot_engagement_note_enabled: false
  hubspot_engagement_task_enabled: false

  # Service
  hubspot_service_enabled: true                           # Enables all service models
  hubspot_ticket_deal_enabled: true

If you are not using a source table that involves freshness tests, please be aware that the feature to disable freshness was only introduced in dbt-core 1.1.0. Therefore ensure the dbt version you're using is v1.1.0 or greater for this config to work.

This package includes all source columns defined in the macros folder. Models by default only bring in a few fields for the company, contact, deal, and ticket tables. You can add more columns using our pass-through column variables. These variables allow for the pass-through fields to be aliased (alias) and casted (transform_sql) if desired, but not required. Datatype casting is configured via a sql snippet within the transform_sql key. You may add the desired sql while omitting the as field_name at the end and your custom pass-though fields will be casted accordingly. Use the below format for declaring the respective pass-through variables within your root dbt_project.yml.

vars:
  hubspot__deal_pass_through_columns:
    - name:           "property_field_new_id"
      alias:          "new_name_for_this_field_id"
      transform_sql:  "cast(new_name_for_this_field as int64)"
    - name:           "this_other_field"
      transform_sql:  "cast(this_other_field as string)"
  hubspot__contact_pass_through_columns:
    - name:           "wow_i_can_add_all_my_custom_fields"
  hubspot__company_pass_through_columns:
    - name:           "this_is_radical"
      alias:          "radical_field"
      transform_sql:  "cast(radical_field as string)"
  hubspot__ticket_pass_through_columns:
    - name:           "property_mmm"
      alias:          "mmm"
    - name:           "property_bop"
      alias:          "bop"

Alternatively, if you would like to simply pass through all columns in the above four tables, add the following configuration to your dbt_project.yml. Note that this will override any hubspot__[table_name]_pass_through_columns variables.

vars:
  hubspot__pass_through_all_columns: true # default is false

This package also provides the ability to pass calculated fields through to the company, contact, deal, and ticket staging models. If you would like to add a calculated field to any of the mentioned staging models, you may configure the respective hubspot__[table_name]_calculated_fields variables with the name of the field you would like to create, and the transform_sql which will be the actual calculation that will make up the calculated field.

vars:
  hubspot__deal_calculated_fields:
    - name:          "deal_calculated_field"
      transform_sql: "existing_field * other_field"
  hubspot__company_calculated_fields:
    - name:          "company_calculated_field"
      transform_sql: "concat(name_field, '_company_name')"
  hubspot__contact_calculated_fields:
    - name:          "contact_calculated_field"
      transform_sql: "contact_revenue - contact_expense"
  hubspot__ticket_calculated_fields:
    - name:          "ticket_calculated_field"
      transform_sql: "total_field / other_total_field"

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

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

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:

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

vars:
    hubspot_<default_source_table_name>_identifier: your_table_name 

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.

This dbt package is dependent on the following dbt packages. Please be aware that these dependencies are installed by default within this package. For more information on the following packages, refer to the dbt hub site.

IMPORTANT: If you have any of these dependent packages in your own packages.yml file, we highly recommend that you remove them from your root packages.yml to avoid package version conflicts.

packages:
    - package: fivetran/fivetran_utils
      version: [">=0.4.0", "<0.5.0"]
    - package: dbt-labs/dbt_utils
      version: [">=1.0.0", "<2.0.0"]
    - package: dbt-labs/spark_utils
      version: [">=0.3.0", "<0.4.0"]

The Fivetran team maintaining this package only maintains the latest version of the package. We highly recommend that you stay consistent with the latest version of the package and refer to the CHANGELOG and release notes for more information on changes across versions.

A small team of analytics engineers at Fivetran develops these dbt packages. However, the packages are made better by community contributions!

We highly encourage and welcome contributions to this package. Check out this dbt Discourse article to learn how to contribute to a dbt package!

• If you have questions or want to reach out for help, please refer to the GitHub Issue section to find the right avenue of support for you.
• If you would like to provide feedback to the dbt package team at Fivetran or would like to request a new dbt package, fill out our Feedback Form.
• Have questions or want to just say hi? Book a time during our office hours on Calendly or email us at [email protected].