Apple App Store Source dbt Package (Docs)
- Materializes Apple App Store staging tables which leverage data in the format described by this ERD. These staging tables clean, test, and prepare your Apple App Store data from Fivetran's connector for analysis by doing the following:
- Name columns for consistency across all packages and for easier analysis
- Adds freshness tests to source data
- Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
- Generates a comprehensive data dictionary of your Apple App Store data through the dbt docs site.
- These tables are designed to work simultaneously with our Apple App Store transformation package.
To use this dbt package, you must have the following:
- At least one Fivetran Apple App Store connection syncing data into your destination.
- A BigQuery, Snowflake, Redshift, PostgreSQL, or Databricks destination.
Include the following apple_store_source 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_source
version: [">=0.4.0", "<0.5.0"] # we recommend using ranges to capture non-breaking changes automatically
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
Your Apple App Store connection may 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
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.
Expand/collapse configurations
If you have multiple apple_store connections 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 definedsource.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.
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>'
By default, this package builds the Apple App Store staging models within a schema titled (<target_schema> + _apple_store_source
) in your target database. If this is not where you would like your Apple App Store staging 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
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
Expand to view 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.
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/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 only maintains the latest version of the package. We highly recommend that 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.
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.
- 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.