Releases: fivetran/dbt_salesforce_marketing_cloud
Release list
v0.6.0 dbt_salesforce_marketing_cloud
PR #19 includes the following updates:
Schema/Data Changes (--full-refresh required after upgrading)
1 total change • 1 possible breaking change
| Data Model(s) | Change type | Old | New | Notes |
|---|---|---|---|---|
| All models | source_relation column (when using a single Salesforce Marketing Cloud schema) |
Empty string ('') |
<database>.<schema> |
Feature Updates
- Introduces the new (recommended)
salesforce_marketing_cloud_sourcesvariable for more robust union data configuration. The oldsalesforce_marketing_cloud_union_schemasandsalesforce_marketing_cloud_union_databasesvariables will still be supported. See the README for specific details.
Under the Hood
- Adds the
fivetran_using_source_casingvariable for case-sensitive destination support. When enabled, downstream transformations respect source casing to ensure consistent results. See the Additional Configurations section of the README for details. - Introduces
fivetran_utils.partition_by_source_relationto conditionally includesource_relationin partition clauses only when multiple sources are configured.
Full Changelog: v0.5.1...v0.6.0
v0.5.1 dbt_salesforce_marketing_cloud
PR #16 includes the following updates:
Bug Fix
- Corrects the identifier for the
triggered_sendsource table. Previously, this was pointing to thesendtable.
Under the Hood
- Nests the
enabledattribute underconfig:for relevant source tables in thesrc_salesforce_marketing_cloud.ymlfile to align with recent dbt updates. - Adds consistency data validation tests for all end models.
Full Changelog: v0.5.0...v0.5.1
v0.5.0 dbt_salesforce_marketing_cloud
PR #14 includes the following updates:
Documentation
- Updates README with standardized Fivetran formatting.
Under the Hood
- In the
quickstart.ymlfile:- Adds
table_variablesfor relevant sources to prevent missing sources from blocking downstream Quickstart models.
- Adds
Full Changelog: v0.4.0...v0.5.0
v0.4.0 dbt_salesforce_marketing_cloud
PR #13 includes the following updates:
Features
- Increases the required dbt version upper limit to v3.0.0
Full Changelog: v0.3.0...v0.4.0
v0.3.0 dbt_salesforce_marketing_cloud
PR #12 includes the following updates:
dbt Fusion Compatibility Updates
- Updated package to maintain compatibility with dbt-core versions both before and after v1.10.6, which introduced a breaking change to multi-argument test syntax (e.g.,
unique_combination_of_columns). - Temporarily removed unsupported tests to avoid errors and ensure smoother upgrades across different dbt-core versions. These tests will be reintroduced once a safe migration path is available.
- Removed all
dbt_utils.unique_combination_of_columnstests. - Moved
loaded_at_field: _fivetran_syncedunder theconfig:block insrc_salesforce_marketing_cloud.yml.
- Removed all
Under the Hood
- Updated conditions in
.github/workflows/auto-release.yml. - Added
.github/workflows/generate-docs.yml.
Documentation
- Added Quickstart model counts to README. (#8)
- Corrected references to connectors and connections in the README. (#8)
Full Changelog: v0.2.0...v0.3.0
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-refreshafter upgrading to this version to avoid possible incremental failures.
- For Databricks All-Purpose clusters, the
salesforce_marketing_cloud__events_enhancedmodel 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_enhancedmodel.
Under the Hood
- The
is_incremental_compatiblemacro has been added to the package. This macro will returntrueif 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_overwriteincremental strategy used in thesalesforce_marketing_cloud__events_enhancedmodel.
- This update was applied as there are other Databricks runtimes (ie. sql warehouse, endpoint, and external runtime) which do not support the
- In addition to the above, for Databricks users the
salesforce_marketing_cloud__events_enhancedmodel 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_testsfolder to ensure the consistency and integrity of thesalesforce_marketing_cloud__events_enhancedmodel 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
idto<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.