Apple App Store Transformation dbt Package (Docs)

What does this dbt package do?

Produces modeled tables that leverage Apple App Store data from Fivetran's connector in the format described by this ERD and build off the output of our Apple App Store source package.
Enables you to better understand your Apple App Store metrics at different granularities. It achieves this by:
- Providing intuitive reporting at the App Version, Platform Version, Device, Source Type, Territory, Subscription and Overview levels
- Aggregates all relevant application metrics into each of the reporting levels above
Generates a comprehensive data dictionary of your source and modeled Apple App Store 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
apple_store__app_version_report	Each record represents daily metrics for each by app_id, source_type and app version.
apple_store__device_report	Each record represents daily subscription metrics by app_id, source_type and device.
apple_store__overview_report	Each record represents daily metrics for each app_id.
apple_store__platform_version_report	Each record represents daily metrics for each by app_id, source_type and platform version.
apple_store__source_type_report	Each record represents daily metrics by app_id and source_type.
apple_store__subscription_report	Each record represents daily subscription metrics by account, app, subscription name, country and state.
apple_store__territory_report	Each record represents daily subscription metrics by app_id, source_type and territory.

How do I use the dbt package?

Step 1: Prerequisites

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

At least one Fivetran Apple App Store connector syncing data into your destination.
A BigQuery, Snowflake, Redshift, PostgreSQL, or Databricks destination.

Step 2: Install the package

Include the following apple_store 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/apple_store
    version: [">=0.4.0", "<0.5.0"] # we recommend using ranges to capture non-breaking changes automatically

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

Step 3: Define database and schema variables

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

vars:
    apple_store_database: your_destination_name
    apple_store_schema: your_schema_name

Step 4: Disable models for non-existent sources

Your Apple App Store connector might not sync every table that this package expects. If you use subscriptions and have the sales_subscription_event_summary and sales_subscription_summary tables synced, add the following variable to your dbt_project.yml file:

vars:
  apple_store__using_subscriptions: true # by default this is assumed to be false

Step 5: Seed `country_codes` mapping table (once)

In order to map longform territory names to their ISO country codes, we have adapted the CSV from lukes/ISO-3166-Countries-with-Regional-Codes to align with Apple's country output format.

You will need to dbt seed the apple_store_country_codes file just once.

(Optional) Step 6: Additional configurations

Expand/collapse configurations

Union multiple connectors

If you have multiple apple_store connectors in Fivetran and would like to use this package on all of them simultaneously, we have provided functionality to do so. The package will union all of the data together and pass the unioned table into the transformations. You will be able to see which source it came from in the source_relation column of each model. To use this functionality, you will need to set either the apple_store_union_schemas OR apple_store_union_databases variables (cannot do both) in your root dbt_project.yml file:

vars:
    apple_store_union_schemas: ['apple_store_usa','apple_store_canada'] # use this if the data is in different schemas/datasets of the same database/project
    apple_store_union_databases: ['apple_store_usa','apple_store_canada'] # use this if the data is in different databases/projects but uses the same schema name

NOTE: The native source.yml connection set up in the package will not function when the union schema/database feature is utilized. Although the data will be correctly combined, you will not observe the sources linked to the package models in the Directed Acyclic Graph (DAG). This happens because the package includes only one defined source.yml.

To connect your multiple schema/database sources to the package models, follow the steps outlined in the Union Data Defined Sources Configuration section of the Fivetran Utils documentation for the union_data macro. This will ensure a proper configuration and correct visualization of connections in the DAG.

Defining subscription events

By default, Subscribe, Renew and Cancel subscription events are included and required in this package for downstream usage. If you would like to add additional subscription events, please add the below to your dbt_project.yml:

    apple_store__subscription_events:
    - 'Renew'
    - 'Cancel'
    - 'Subscribe'
    - '<additional_event_name>'
    - '<additional_event_name>'

Change the build schema

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

models:
    apple_store_source:
      +schema: my_new_schema_name # leave blank for just the target_schema
    apple_store:
      +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:
    apple_store_<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. 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/apple_store_source
      version: [">=0.4.0", "<0.5.0"]

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

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

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.

Opinionated Decisions

In creating this package, which is meant for a wide range of use cases, we had to take opinionated stances on a few different questions we came across during development. We've consolidated significant choices we made in the DECISIONLOG.md, and will continue to update as the package evolves. We are always open to and encourage feedback on these choices, and the package in general.

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.