v0.2.0 dbt_salesforce_marketing_cloud

PR #4 includes the following updates. Please be aware these changes only impact Databricks warehouse users:

🚨 Breaking Changes 🚨

⚠️ Since the following changes result in the table format changing for Databricks users, we recommend running a --full-refresh after upgrading to this version to avoid possible incremental failures.

• For Databricks All-Purpose clusters, the salesforce_marketing_cloud__events_enhanced model will now be materialized using the delta table format (previously parquet).
  • Delta tables are generally more performant than parquet and are also more widely available for Databricks users. Previously, the parquet file format was causing compilation issues on customers' managed tables.

Documentation

• Added details to the README to highlight the incremental strategies used within the salesforce_marketing_cloud__events_enhanced model.

Under the Hood

• The is_incremental_compatible macro has been added to the package. This macro will return true if the Databricks runtime being used is an all-purpose cluster or if any other non-Databricks supported destination is being used.
  • This update was applied as there are other Databricks runtimes (ie. sql warehouse, endpoint, and external runtime) which do not support the insert_overwrite incremental strategy used in the salesforce_marketing_cloud__events_enhanced model.
• In addition to the above, for Databricks users the salesforce_marketing_cloud__events_enhanced model will now leverage the incremental strategy only if the Databricks runtime is all-purpose. Otherwise, all other Databricks runtimes will not leverage an incremental strategy.
• Added validation tests to the integration_tests folder to ensure the consistency and integrity of the salesforce_marketing_cloud__events_enhanced model for subsequent updates.

Full Changelog: v0.1.0...v0.2.0

v0.1.0 dbt_salesforce_marketing_cloud

🎉 This is the initial release of this package! 🎉

📣 What does this dbt package do?

This package models Salesforce Marketing Cloud data from Fivetran's connector. It uses data in the format described by this ERD.

The main focus of the package is to transform the core object tables into analytics-ready models:

• Materializes Salesforce Marketing Cloud staging tables which leverage data in the format described by this ERD. The staging tables clean, test, and prepare your Salesforce Marketing Cloud data from Fivetran's connector for analysis by doing the following:
• Primary keys are renamed from id to <table name>_id.
• Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
• Provides insight into your Salesforce Marketing Cloud data across the following grains:
  • Email, send, event, link, list, and subscriber
• Generates a comprehensive data dictionary of your Salesforce Marketing Cloud data through the dbt docs site.