• Produces modeled tables that leverage Recharge data from Fivetran's connector in the format described by this ERD and build off the output of our Recharge source package.
• Enables you to better understand your Recharge data by summarizing customer, revenue, and subscription trends.
• Generates a comprehensive data dictionary of your source and modeled Recharge 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.

An example churn model is separately available in the analysis folder:

Curious what these models can do? Check out example visualizations from the recharge__line_item_enhanced model in the Fivetran Billing Model Streamlit App, and see how you can use these models in your own reporting. Below is a screenshot of an example report—-explore the app for more.

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

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

Include the following recharge 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/recharge
    version: [">=0.3.0", "<0.4.0"] # we recommend using ranges to capture non-breaking changes automatically

Do NOT include the recharge_source package in this file. The transformation package itself has a dependency on it and will install the source package as well.

If you are using a Databricks destination with this package, you must add the following dispatch configuration (or a variation thereof) within your dbt_project.yml. This is required for the package to accurately search for macros within the dbt-labs/spark_utils package, then the dbt-labs/dbt_utils package, respectively.

dispatch:
  - macro_namespace: dbt_utils
    search_order: ['spark_utils', 'dbt_utils']

By default, this package runs using your destination and the recharge schema. If your Recharge data is in a different database or schema (for example, if your Recharge schema is named recharge_fivetran), add the following configuration to your root dbt_project.yml file:

vars:
  recharge_database: your_destination_name
  recharge_schema: your_schema_name 

Your Recharge connector may not sync every table that this package expects. If you do not have the CHECKOUT, ONE_TIME_PRODUCT and/or CHARGE_TAX_LINE tables synced, add the corresponding variable(s) to your root dbt_project.yml file to disable these sources:

vars:
  recharge__one_time_product_enabled: false # Disables if you do not have the ONE_TIME_PRODUCT table. Default is True.
  recharge__charge_tax_line_enabled: false # Disables if you do not have the CHARGE_TAX_LINE table. Default is True.
  recharge__checkout_enabled: true # Enables if you do have the CHECKOUT table. Default is False.

vars:
  recharge__standardized_billing_model_enabled: true # false by default.

vars:
  recharge__using_orders: false # default is true, which will use the `orders` version of the source.

vars:
    recharge_first_date: "yyyy-mm-dd"
    recharge_last_date: "yyyy-mm-dd"

vars:
    recharge__address_passthrough_columns: 
      - name: "new_custom_field"
        alias: "custom_field_name"
        transform_sql:  "cast(custom_field_name as int64)"
      - name: "a_second_field"
        transform_sql:  "cast(a_second_field as string)"
    # a similar pattern can be applied to the rest of the following variables.
    recharge__charge_passthrough_columns:
    recharge__charge_line_item_passthrough_columns:
    recharge__checkout_passthrough_columns:
    recharge__order_passthrough_columns:
    recharge__order_line_passthrough_columns:
    recharge__subscription_passthrough_columns:
    recharge__subscription_history_passthrough_columns:

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

vars:
    recharge_<default_source_table_name>_identifier: your_table_name 

vars:
  recharge_order_identifier: '"Order"' # as an example, must include this quoting pattern and adjust for your exact casing

sources:
  tables:
    - name: order 
      # Add the below
      identifier: ORDER # Or what your order table is named, being mindful of casing
      quoting:
        identifier: true

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 root packages.yml to avoid package version conflicts.

packages:
    - package: fivetran/recharge_source
      version: [">=0.3.0", "<0.4.0"]

    - package: fivetran/fivetran_utils
      version: [">=0.4.0", "<0.5.0"]

    - package: dbt-labs/dbt_utils
      version: [">=1.0.0", "<2.0.0"]

The Fivetran team maintaining this package maintains only the latest version of the package. We highly recommend that you consistently use the latest version of the package and refer to the CHANGELOG and release notes for more information about changes.

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.

This dbt package takes an opinionated stance on revenue is calculated, using charges in some cases and orders in others. If you would like a deeper explanation of the logic used by default in the dbt package, you may reference the DECISIONLOG.

• 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.