Hubspot (Source)

This package models Hubspot data from Fivetran's connector. It uses data in the format described by the marketing, sales and service ERDs.

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

Models

This package contains staging models, designed to work simultaneously with our Hubspot modeling package. The staging models:

• Remove any rows that are soft-deleted
• 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 user table's ID column is renamed user_id.

Installation Instructions

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

Configuration

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

# dbt_project.yml

...
config-version: 2

vars:
  hubspot_source:
    hubspot_database: your_database_name
    hubspot_schema: your_schema_name

Disabling models

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. In order to 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 hubspot_service_enabled). You only need to add variables for the tables you would like to disable or enable respectively:

# dbt_project.yml

...
config-version: 2

vars:
  hubspot_source:

    # 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_opens_enabled: false
    hubspot_email_event_print_enabled: false
    hubspot_email_event_sent_enabled: false
    hubspot_email_event_spam_report: false
    hubspot_email_event_status_change_enabled: false

    # Sales

    hubspot_sales_enabled: false                            # Disables all sales models
    hubspot_company_enabled: false
    hubspot_deal_enabled: false
    hubspot_deal_company_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_calls_enabled: false
    hubspot_engagement_emails_enabled: false
    hubspot_engagement_meetings_enabled: false
    hubspot_engagement_notes_enabled: false
    hubspot_engagement_tasks_enabled: false

    # Service
    hubspot_service_enabled:                    true        # Enables all service models

Passthrough Columns

Additionally, this package includes all source columns defined in the macros folder. We highly recommend including custom fields in this package as models now 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.

# 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"

Changing the Build Schema

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

# dbt_project.yml

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

Read more about using custom schemas in dbt here.

Contributions

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

Database Support

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

Resources:

• Provide feedback on our existing dbt packages or what you'd like to see next
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• Learn how to orchestrate dbt transformations with Fivetran
• Learn more about Fivetran overall in our docs
• Check out Fivetran's blog
• Learn more about dbt in the dbt docs
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