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Releases: fivetran/dbt_salesforce_marketing_cloud

v0.6.0 dbt_salesforce_marketing_cloud

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@fivetran-data-model-bot fivetran-data-model-bot released this 23 Jun 21:04
9f55a85

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_sources variable for more robust union data configuration. The old salesforce_marketing_cloud_union_schemas and salesforce_marketing_cloud_union_databases variables will still be supported. See the README for specific details.

Under the Hood

  • Adds the fivetran_using_source_casing variable 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_relation to conditionally include source_relation in partition clauses only when multiple sources are configured.

Full Changelog: v0.5.1...v0.6.0

v0.5.1 dbt_salesforce_marketing_cloud

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@fivetran-data-model-bot fivetran-data-model-bot released this 23 Feb 16:51
a04230b

PR #16 includes the following updates:

Bug Fix

  • Corrects the identifier for the triggered_send source table. Previously, this was pointing to the send table.

Under the Hood

  • Nests the enabled attribute under config: for relevant source tables in the src_salesforce_marketing_cloud.yml file 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

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@fivetran-data-model-bot fivetran-data-model-bot released this 20 Jan 16:06
721684e

PR #14 includes the following updates:

Documentation

  • Updates README with standardized Fivetran formatting.

Under the Hood

  • In the quickstart.yml file:
    • Adds table_variables for relevant sources to prevent missing sources from blocking downstream Quickstart models.

Full Changelog: v0.4.0...v0.5.0

v0.4.0 dbt_salesforce_marketing_cloud

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@fivetran-data-model-bot fivetran-data-model-bot released this 01 Dec 22:05
f543919

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

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@fivetran-data-model-bot fivetran-data-model-bot released this 14 Aug 16:27
d26374c

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_columns tests.
    • Moved loaded_at_field: _fivetran_synced under the config: block in src_salesforce_marketing_cloud.yml.

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

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@fivetran-data-model-bot fivetran-data-model-bot released this 17 Jul 19:51
8cf68f5

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

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@fivetran-data-model-bot fivetran-data-model-bot released this 18 Jan 18:12

🎉 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.