Stripe Transformation dbt Package (Docs)

📣 What does this dbt package do?

• Produces modeled tables that leverage Stripe data from Fivetran's connector in the format described by this ERD and build off the output of our stripe source package.
• Enables you to better understand your Stripe transactions. The package achieves this by performing the following:
  • Enhance the balance transaction entries with useful fields from related tables.
  • Generate a metrics tables allow you to better understand your account activity over time or at a customer level. These time-based metrics are available on a daily, weekly, monthly, and quarterly level.
• Generates a comprehensive data dictionary of your source and modeled Stripe data through the dbt docs site.

The following table provides a detailed list of all models materialized within this package by default.

TIP: See more details about these models in the package's dbt docs site.

model	description
stripe__balance_transactions	Each record represents a change to your account balance, enriched with data about the transaction.
stripe__invoice_line_items	Each record represents an invoice line item, enriched with details about the associated charge, customer, subscription, and plan.
stripe__subscription_details	Each record represents a subscription, enriched with customer details and payment aggregations.
stripe__subscription_line_items	Each record represents a subscription invoice line item, enriched with details about the associated charge, customer, subscription, and plan. Use this table as the starting point for your company-specific churn and MRR calculations.
stripe__customer_overview	Each record represents a customer, enriched with metrics about their associated transactions. Transactions with no associated customer will have a customer description of "No associated customer".
stripe__daily_overview	Each record represents a single day, enriched with metrics about balances, payments, refunds, payouts, and other transactions.
stripe__weekly_overview	Each record represents a single week, enriched with metrics about balances, payments, refunds, payouts, and other transactions.
stripe__monthly_overview	Each record represents a single month, enriched with metrics about balances, payments, refunds, payouts, and other transactions.
stripe__quarterly_overview	Each record represents a single quarter, enriched with metrics about balances, payments, refunds, payouts, and other transactions.

🎯 How do I use the dbt package?

Step 1: Prerequisites

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

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

Step 2: Install the package

Include the following stripe 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/stripe
    version: [">=0.8.0", "<0.9.0"]

Step 3: Define database and schema variables

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

vars:
    stripe_database: your_destination_name
    stripe_schema: your_schema_name 

Step 4: Disable models for non-existent sources

This package takes into consideration that not every Stripe account utilizes the invoice, invoice_line_item, payment_method, payment_method_card, plan, or subscription features, and allows you to disable the corresponding functionality. By default, all variables' values are assumed to be true. Add variables for only the tables you want to disable within your root dbt_project.yml:

vars:
    using_invoices:        False  #Disable if you are not using the invoice and invoice_line_item tables
    using_payment_method:  False  #Disable if you are not using the payment_method and payment_method_card tables
    using_subscriptions:   False  #Disable if you are not using the subscription and plan tables.

Step 5: Leveraging Subscription Vs Subscription History Sources

For Stripe connectors set up after February 09, 2022 the subscription table has been replaced with the new subscription_history table. By default this package will look for your subscription data within the subscription source table. However, if you have a newer connector then you must leverage the stripe__subscription_history to have the package use the subscription_history source rather than the subscription table.

Please note that if you have stripe__subscription_history enabled then the package will filter for only active records.

vars:
    stripe__subscription_history: True  # False by default. Set to True if your connector syncs the `subscription_history` table. 

(Optional) Step 6: Additional configurations

Expand for configurations

Setting your timezone

This packages leaves all timestamp columns in the UTC timezone. However, there are certain instances, such in the daily overview model, that timestamps have to be converted to dates. As a result, the timezone used for the timestamp becomes relevant. By default, this package will use the UTC timezone when converting to date, but if you want to set the timezone to the time in your Stripe reports, add the following configuration to your root dbt_project.yml:

vars:
  stripe_timezone: "America/New_York" # Replace with your timezone

Running on Live vs Test Customers

By default, this package will run on non-test data (where livemode = true) from the source Stripe tables. However, you may want to include and focus on test data when testing out the package or developing your analyses. To run on only test data, add the following configuration to your root dbt_project.yml file:

vars:
    stripe_source:
        using_livemode: false  # Default = true

Including sub Invoice Line Items

By default, this package will filter out any records from the invoice_line_item source table which include the string sub_. This is due to a legacy Stripe issue where sub_ records were found to be duplicated. However, if you highly utilize these records you may wish they be included in the final output of the stg_stripe__invoice_line_item model. To do, so you may include the below variable configuration in your root dbt_project.yml:

vars:
    stripe_source:
        using_invoice_line_sub_filter: false # Default = true

Pivoting out Metadata Properties

Oftentimes you may have custom fields within your source tables that is stored as a JSON object that you wish to pass through. By leveraging the metadata variable, this package pivot out fields into their own columns. The metadata variables accept dictionaries in addition to strings.

Additionally, if you happen to be using a reserved word as a metadata field, any otherwise incompatible name, or just wish to rename your field, Below are examples of how you would add the respective fields.

The metadata JSON field is present within the customer, charge, invoice, payment_intent, payment_method, payout, plan, refund, and subscription source tables. To pivot these fields out and include in the respective downstream staging model, add the respective variable(s) to your root dbt_project.yml file like below.

vars: 
  stripe__charge_metadata:
    - name: metadata_field_1
  stripe__invoice_metadata: 
    - name: metadata_field_2
  stripe__payment_intent_metadata:
    - name: incompatible.field
      alias: rename_incompatible_field
  stripe__payment_method_metadata:
    - name: field_is_reserved_word
      alias: field_is_reserved_word_xyz
  stripe__payout_metadata:
    - name: 123
      alias: one_two_three
  stripe__plan_metadata:
    - name: rename
    - alias: renamed_field
  stripe__refund_metadata:
    - name: metadata_field_3
    - name: metadata_field_4
  stripe__subscription_metadata:
    - name: metadata_field_5
  stripe__customer_metadata:
    - name: metadata_field_6

Alternatively, if you only have strings in your JSON object, the metadata variable accepts the following configuration as well.

Note: stripe__plan_metadata is only shown below, but the format will work for all metadata variables.

vars:
    stripe__plan_metadata: ['the', 'list', 'of', 'property', 'fields'] # Note: this is case-SENSITIVE and must match the casing of the property as it appears in the JSON

Change the build schema

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

models:
    stripe_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:
    stripe_<default_source_table_name>_identifier: your_table_name 

(Optional) Step 7: 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. 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/stripe_source
      version: [">=0.8.0", "<0.9.0"]

    - 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, 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 solutions@fivetran.com.