HubSpot Transformation dbt Package (Docs)
What does this dbt package do?
- Produces modeled tables that leverage HubSpot data from Fivetran's connector in the format described by this ERD and build off the output of our HubSpot source package.
- Enables you to better understand your HubSpot email and engagement performance. The package achieves this by performing the following:
- Generates models for contacts, companies, and deals with enriched email and engagement metrics.
- Provides analysis-ready event tables for email and engagement activities.
- Generates a comprehensive data dictionary of your source and modeled HubSpot data through the dbt docs site.
The following table provides a detailed list of all tables materialized within this package by default.
TIP: See more details about these tables in the package's dbt docs site.
Table | Description |
---|---|
hubspot__companies | Each record represents a company in Hubspot, enriched with metrics about engagement activities. |
hubspot__company_history | Each record represents a change to a company in Hubspot, with valid_to and valid_from information. |
hubspot__contacts | Each record represents a contact in Hubspot, enriched with metrics about email and engagement activities. |
hubspot__contact_history | Each record represents a change to a contact in Hubspot, with valid_to and valid_from information. |
hubspot__contact_lists | Each record represents a contact list in Hubspot, enriched with metrics about email activities. |
hubspot__deals | Each record represents a deal in Hubspot, enriched with metrics about engagement activities. |
hubspot__deal_stages | Each record represents when a deal stage changes in Hubspot, enriched with metrics about deal activities. |
hubspot__deal_history | Each record represents a change to a deal in Hubspot, with valid_to and valid_from information. |
hubspot__tickets | Each record represents a ticket in Hubspot, enriched with metrics about engagement activities and information on associated deals, contacts, companies, and owners. |
hubspot__daily_ticket_history | Each record represents a ticket's day in Hubspot with tracked properties pivoted out into columns. |
hubspot__email_campaigns | Each record represents a email campaign in Hubspot, enriched with metrics about email activities. |
hubspot__email_event_* | Each record represents an email event in Hubspot, joined with relevant tables to make them analysis-ready. |
hubspot__email_sends | Each record represents a sent email in Hubspot, enriched with metrics about opens, clicks, and other email activity. |
hubspot__engagement_* | Each record represents an engagement event in Hubspot, joined with relevant tables to make them analysis-ready. |
How do I use the dbt package?
Step 1: Prerequisites
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.
Databricks Dispatch Configuration
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']
Database Incremental Strategies
Many of the models in this package are materialized incrementally, so we have configured our models to work with the different strategies available to each supported warehouse.
For BigQuery and Databricks All Purpose Cluster runtime destinations, we have chosen insert_overwrite
as the default strategy, which benefits from the partitioning capability.
For Databricks SQL Warehouse destinations, models are materialized as tables without support for incremental runs.
For Snowflake, Redshift, and Postgres databases, we have chosen delete+insert
as the default strategy.
Regardless of strategy, we recommend that users periodically run a
--full-refresh
to ensure a high level of data quality.
Step 2: Install the package
Include the following hubspot 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
version: [">=0.18.0", "<0.19.0"] # we recommend using ranges to capture non-breaking changes automatically
Do NOT include the hubspot_source
package in this file. The transformation package itself has a dependency on it and will install the source package as well.
Databricks dispatch configuration
If you are using a Databricks destination with this package, you must add the following (or a variation of the following) 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']
Step 3: Define database and schema variables
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
Step 4: Disable models for non-existent sources
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
, hubspot_ticket_deal_enabled
, hubspot_contact_merge_audit_enabled
, and hubspot_merged_deal_enabled
). You only need to add variables within your root dbt_project.yml
for the tables you would like to disable or enable respectively:
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_contact_property_history_enabled: false # Disables the contact property history 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_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 the use of the CONTACT_MERGE_AUDIT table (deprecated by Hubspot v3 API) for removing merged contacts in the final models.
# If false, ~~~contacts will still be merged~~~, but using the CONTACT.property_hs_calculated_merged_vids field (introduced in v3 of the Hubspot CRM API)
# Default = false
# Sales
hubspot_sales_enabled: false # Disables all sales models
hubspot_company_enabled: false
hubspot_company_property_history_enabled: false # Disables the company property history models
hubspot_deal_enabled: false
hubspot_merged_deal_enabled: true # Enables the merged_deal table, which will be used to filter out merged deals from the final deal models. False by default. Note that `hubspot_sales_enabled` and `hubspot_deal_enabled` must not be set to False.
hubspot_deal_company_enabled: false
hubspot_deal_contact_enabled: false
hubspot_deal_property_history_enabled: false # Disables the deal property history models
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
hubspot_owner_enabled: false
hubspot_property_enabled: false # Disables property and property_option tables
# Service
hubspot_service_enabled: true # Enables all service/ticket models. Default = false
hubspot_ticket_deal_enabled: true # Default = false
(Optional) Step 5: Additional configurations
Configure email metrics
This package allows you to specify which email metrics (total count and total unique count) you would like to be calculated for specified fields within the hubspot__email_campaigns
model. By default, the email_metrics
variable below includes all the shown fields. If you would like to remove any field metrics from the final model, you may copy and paste the below snippet within your root dbt_project.yml
and remove any fields you want to be ignored in the final model.
vars:
email_metrics: ['bounces', #Remove if you do not want metrics in final model.
'clicks', #Remove if you do not want metrics in final model.
'deferrals', #Remove if you do not want metrics in final model.
'deliveries', #Remove if you do not want metrics in final model.
'drops', #Remove if you do not want metrics in final model.
'forwards', #Remove if you do not want metrics in final model.
'opens', #Remove if you do not want metrics in final model.
'prints', #Remove if you do not want metrics in final model.
'spam_reports', #Remove if you do not want metrics in final model.
'unsubscribes' #Remove if you do not want metrics in final model.
]
Include passthrough columns
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 in 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"
alias: "best_field"
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
Adding property label
For property_hs_*
columns, you can enable the corresponding, human-readable property_option
.label
to be included in the staging models.
Important
- You must have sources
property
andproperty_option
enabled to enable labels. By default, these sources are enabled. - You CANNOT enable labels if using
hubspot__pass_through_all_columns: true
. - We recommend being selective with the label columns you add. As you add more label columns, your run time will increase due to the underlying logic requirements.
To enable labels for a given property, set the property attribute add_property_label: true
, using the below format.
vars:
hubspot__ticket_pass_through_columns:
- name: "property_hs_fieldname"
alias: "fieldname"
add_property_label: true
Alternatively, you can enable labels for all passthrough properties by using variable hubspot__enable_all_property_labels: true
, formatted like the below example.
vars:
hubspot__enable_all_property_labels: true
hubspot__ticket_pass_through_columns:
- name: "property_hs_fieldname1"
- name: "property_hs_fieldname2"
Including calculated fields
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"
Filtering email events
When leveraging email events, HubSpot customers may take advantage of filtering out specified email events. These filtered email events are present within the stg_hubspot__email_events
model and are identified by the is_filtered_event
boolean field. By default, these events are included in the staging and downstream models generated from this package. However, if you wish to remove these filtered events you may do so by setting the hubspot_using_all_email_events
variable to false. See below for exact configurations you may provide in your dbt_project.yml
file:
vars:
hubspot_using_all_email_events: false # True by default
Daily ticket history
The hubspot__daily_ticket_history
model is disabled by default, but will materialize if hubspot_service_enabled
is set to true
. See additional configurations for this model below.
Note:
hubspot__daily_ticket_history
and its parent intermediate models are incremental. After making any of the below configurations, you will need to run a full refresh.
Tracking ticket properties
By default, hubspot__daily_ticket_history
will track each ticket's state, pipeline, and pipeline stage and pivot these properties into columns. However, any property from the source TICKET_PROPERTY_HISTORY
table can be tracked and pivoted out into columns. To add other properties to this end model, add the following configuration to your dbt_project.yml
file:
vars:
hubspot__ticket_property_history_columns:
- the
- list
- of
- property
- names
Extending ticket history past closing date
This package will create a row in hubspot__daily_ticket_history
for each day that a ticket is open, starting at its creation date. A Hubspot ticket can be altered after being closed, so its properties can change after this date.
By default, the package will track a ticket up to its closing date (or the current date if still open). To capture post-closure changes, you may want to extend a ticket's history past the close date. To do so, add the following configuration to your root dbt_project.yml file:
vars:
hubspot:
ticket_history_extension_days: integer_number_of_days # default = 0
Changing the Build Schema
By default this package will build the HubSpot staging models within a schema titled (<target_schema> + _stg_hubspot
) and HubSpot final models within a schema titled (<target_schema> + hubspot
) in your target database. If this is not where you would like your modeled HubSpot data to be written to, add the following configuration to your root dbt_project.yml
file:
models:
hubspot:
+schema: my_new_schema_name # leave blank for just the target_schema
hubspot_source:
+schema: my_new_schema_name # leave blank for just the target_schema
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:
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
(Optional) Step 6: Orchestrate your models with Fivetran Transformations for dbt Core™
Expand for details
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.
Does this package have dependencies?
This dbt package is dependent on the following dbt packages. 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 rootpackages.yml
to avoid package version conflicts.
packages:
- package: fivetran/hubspot_source
version: [">=0.15.0", "<0.16.0"]
- 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"]
How is this package maintained and can I contribute?
Package Maintenance
The Fivetran team maintaining this package only maintains the latest version of the package. We highly recommend 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.
Contributions
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 on the best workflow for contributing to a package.
Are there any resources available?
- If you have questions or want to reach out for help, see 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.