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This packages aims to transform the RevenueCat data to cookiecutter datasets ready for analysis. This package does require to have the RevenueCat scheduled data exports enabled and loaded into Snowflake.
Key Features:
- 🔥 Accurate deduplication of RevenueCat transaction data
- 🎉 Transformed core model set for transactions, activities, entitlements and products.
- 🏃 Out-of-the-box analysis models that align with RevenueCat's UI reporting logic.
To get started specify the location of the table in Snowflake by setting the variables revenuecat_database, revenuecat_schema and revenuecat_table. Optionally, it is possible to apply a filter by passing the revenuecat_filter variable. Common practice is to filter the sandbox transactions out of the analysis data. To parse the custom subscriber attributes specify the revenuecat_custom_subscriber_attributes dictionary with key, value pairs for the values to parse and the column names to provide it.
vars:
tasman_dbt_revenuecat:
revenuecat_database: "source_db"
revenuecat_schema: 'revenuecat'
revenuecat_table: "data_export"
revenuecat_verson: 5
revenuecat_filter: "is_sandbox = false"
revenuecat_custom_subscriber_attributes: {'my_value::text': 'my_column_name'}
This package currently only supports Snowflake.
This package has been written and is maintained by Tasman Analytics.
If you find a bug, or for any questions please open an issue on GitHub.