v0.10.0 dbt_linkedin_source

PR #69 includes the following updates:

Breaking Changes

• The click_uri_type field has been added to the stg_linkedin_ads__creative_history model. This field allows users to differentiate which click uri type (text_ad or spotlight) is being used to populate the results of the click_uri field.
  • Please be aware this field only supports text_ad or spotlight click uri types. If you are interested in this package supporting more click uri ad types, please let us know in this Feature Request.

Bug Fixes

• The click_uri field has been adjusted to populate the results following a coalesce on the text_ad_landing_page, spotlight_landing_page, or click_uri fields.
  • This change is in response to a LinkedIn Ads API and Fivetran LinkedIn Ads connector update which moved click_uri data to either the text_ad_landing_page or spotlight_landing_page fields depending on the creative type.
• Updated the is_latest_version window function in the following models to exclude the source_relation field from the partition statement when linkedin_ads_union_schemas or linkedin_ads_union_databases variables are empty in the following models:
  • stg_linkedin_ads__account_history
  • stg_linkedin_ads__campaign_group_history
  • stg_linkedin_ads__campaign_history
  • stg_linkedin_ads__creative_history
• In addition to the above, the is_latest_version window function within the stg_linkedin_ads__creative_history model has been moved to the final cte to avoid possible constant expression errors within Redshift destinations.

Under the Hood

• Updates to the linkedin_creative_history_data seed file to include the following new fields to ensure accurate data validation tests:
  • text_ad_landing_page
  • spotlight_landing_page

Documentation Updates

• Added click_uri_type field documentation.
• The click_uri field documentation has been updated to reflect the updated state of the field.

Full Changelog: v0.9.0...v0.10.0

v0.9.0 dbt_linkedin_source

PR #67 includes the following updates:

🚨 Breaking Changes 🚨

Feature Updates: Conversion Support!

We have added more robust support for conversions in our data models by doing the following:

• Created a linkedin_ads__conversion_fields variable to pass through additional conversion metrics in the stg_linkedin_ads__ad_analytics_by_campaign and stg_linkedin_ads__ad_analytics_by_creative models.
  • Set variable defaults in the dbt_project.yml to bring in the most used conversion fields external_website_conversions and one_click_leads.
• Ensured backwards compatibility with existing passthrough column variables in these models by creating macro checks for whether these fields already are brought in by the existing passthrough variables. This ensures there are no duplicate column errors if both the new conversion variable and the old passthrough variable are leveraged in either stg_linkedin_ads__ad_analytics_by_* data model.
• Brought in the conversion_value_in_local_currency field to the above mentioned stg_linkedin_ads__ad_analytics_by_* models.

The above new field additions are 🚨 breaking changes 🚨 for users who were not already bringing in conversion fields via passthrough columns.

Documentation Update

• Documents the ability to transform metrics provided to the linkedin_ads__campaign_passthrough_metrics and linkedin_ads__creative_passthrough_metrics variables in the README.
• Added new metrics to src and stg yml files.

Under the Hood

• Updated linkedin_ad_analytics_by_creative_data seed file with relevant conversion fields for more robust testing.

Contributors

• Seer Interactive

Full Changelog: v0.8.2...v0.9.0

v0.8.2 dbt_linkedin_source

PR #66 includes the following updates:

Bug Fixes

• Adjusted the logic for determining the values of the is_latest_version, last_modified_at, status, and created_at fields in the stg_linkedin_ads__creative_history model for pre-January 2023 Fivetran connectors.
  • This ensures proper handling of retroactively filled last_modified_at values and maintains consistency in the COALESCE ordering for the status and created_at fields.
  • See the January 2023 Fivetran connector release notes for more information.

Full Changelog: v0.8.1...v0.8.2

v0.8.1 dbt_linkedin_source

PR #64 includes the following updates:

Bug Fixes

• This package now leverages the new linkedin_ads_extract_url_parameter() macro for use in parsing out url parameters. This was added to create special logic for Databricks instances not supported by dbt_utils.get_url_parameter().
  • This macro will be replaced with the fivetran_utils.extract_url_parameter() macro in the next breaking change of this package.

Under the Hood

• Included auto-releaser GitHub Actions workflow to automate future releases.

Full Changelog: v0.8.0...v0.8.1

v0.8.0 dbt_linkedin_source

PR #54 includes the following updates:

Breaking changes

• Updated materializations of non-tmp staging models from views to tables. This is to bring the materializations into alignment with other ad reporting packages and eliminate errors in Redshift.
• Updated the name of the source created by this package from linkedin to linkedin_ads. This was to bring the naming used in this package in alignment with our other ad packages and for compatibility with the union schema feature.
  • ❗ If you are using this source, you will need to update the name.
• Updated the following identifiers for consistency with the source name and compatibility with the union schema feature:

current	previous
linkedin_ads_account_history_identifier	linkedin_account_history_identifier
linkedin_ads_ad_analytics_by_creative_identifier	linkedin_ad_analytics_by_creative_identifier
linkedin_ads_campaign_group_history_identifier	linkedin_campaign_group_history_identifier
linkedin_ads_campaign_history_identifier	linkedin_campaign_history_identifier
linkedin_ads_creative_history_identifier	linkedin_creative_history_identifier
linkedin_ads_ad_analytics_by_campaign_identifier	linkedin_ad_analytics_by_campaign_identifier

• If you are using the previous identifier, be sure to update to the current version!

Feature update 🎉

• Unioning capability! This adds the ability to union source data from multiple linkedin connectors. Refer to the Union Multiple Connectors README section for more details.

Under the hood 🚘

• Updated tmp models to union source data using the fivetran_utils.union_data macro.
• To distinguish which source each field comes from, added source_relation column in each staging model and applied the fivetran_utils.source_relation macro.
• Updated tests to account for the new source_relation column.

PR #51 includes the following updates:

• Incorporated the new fivetran_utils.drop_schemas_automation macro into the end of each Buildkite integration test job.
• Updated the pull request templates.

Full Changelog: v0.7.0...v0.8.0

v0.7.0 dbt_linkedin_source

🚨 Breaking Changes 🚨

Due to Linkedin Ads API change in January 2023, there have been updates in the Linkedin Ads Fivetran Connector and therefore, updates to this Linkedin package.

The following fields have been completely deprecated in the stg_linkedin_ads__creative_history model (PR #48):

• type
• call_to_action_label_type
• version_tag

Updates

PR #48 includes the below modifications:

• The following legacy fields have been updated respectively in the connector:
  • last_modified_time has been updated to last_modified_at
  • created_time has been updated to created_at
  • status has been updated to intended_status
• src_linkedin.yml have been updated to reflect new definitions for the above updated fields.
• Removing unique column testing from stg_linkedin__creative_history as a result of the recent API version update that impacted the CREATIVE_HISTORY table. We were recently made aware of an edge case that results in duplicate records for a given Creative ID due to a primary key change (last_modified_time to last_modified_at). Duplicate data will appear if a creative was deleted from the LinkedIn Ads platform during the API update process -- the likelihood of this happening is small and it would only impact deleted creatives.

Under the Hood

• integration_tests/seeds/linkedin_creative_history_data has been updated to reflect new fields and deprecated fields
• _fivetran_synced field removed from seed data for linkedin_ad_analytics_by_campaign_data integration testing as it is not used in this package's models

dbt_linkedin_source v0.6.0

🚨 Breaking Changes 🚨:

PR #47 includes the following breaking changes:

• Dispatch update for dbt-utils to dbt-core cross-db macros migration. Specifically {{ dbt_utils.<macro> }} have been updated to {{ dbt.<macro> }} for the below macros:
  • any_value
  • bool_or
  • cast_bool_to_text
  • concat
  • date_trunc
  • dateadd
  • datediff
  • escape_single_quotes
  • except
  • hash
  • intersect
  • last_day
  • length
  • listagg
  • position
  • replace
  • right
  • safe_cast
  • split_part
  • string_literal
  • type_bigint
  • type_float
  • type_int
  • type_numeric
  • type_string
  • type_timestamp
  • array_append
  • array_concat
  • array_construct
• For current_timestamp and current_timestamp_in_utc macros, the dispatch AND the macro names have been updated to the below, respectively:
  • dbt.current_timestamp_backcompat
  • dbt.current_timestamp_in_utc_backcompat
• packages.yml has been updated to reflect new default fivetran/fivetran_utils version, previously [">=0.3.0", "<0.4.0"] now [">=0.4.0", "<0.5.0"].

dbt_linkedin_source 0.5.0

PR #46 includes the following changes:

🚨 Breaking Changes 🚨

• ALL staging models and ALL variables now have the prefix linkedin_ads_*. They previously were prepended with linkedin_*. This includes the required schema and database variables. We made this change to better discern between Linkedin Ads and Linkedin Pages.
• Staging models are now by default written within a schema titled (<target_schema> + _linkedin_ads_source) in your destination. Previously, this was titled (<target_schema> + _stg_linkedin).
• The declaration of passthrough variables within your root dbt_project.yml has changed. To allow for more flexibility and better tracking of passthrough columns, you will now want to define passthrough columns in the following format:

vars:
  linkedin_ads__creative_passthrough_metrics: # NOTE that this used to be called linkedin__passthrough_metrics
    - name: "my_field_to_include" # Required: Name of the field within the source.
      alias: "field_alias" # Optional: If you wish to alias the field within the staging model.
  linkedin_ads__campaign_passthrough_metrics: # This will pull from `ad_analytics_by_campaign`
    - name: "my_field_to_include"
      alias: "field_alias"

🎉 Feature Enhancements 🎉

• Addition of the stg_linkedin_ads__ad_analytics_by_campaign model. This is to generate a more accurate representation of Linkedin Ad Analytics data at the campaign level.
• README updates for easier navigation and use of the package.
• Addition of identifier variables for each of the source tables to allow for further flexibility in source table direction within the dbt project.
• Additional columns included in _history staging models.

linkedin_source v0.4.1

Fixes

• All timestamp fields within the staging models have been cast using {{ dbt_utils.type_timestamp() }}. This is needed as the timestamps need to be consistently cast in order for downstream date functions to succeed.

linkedin_source 0.4.0

🎉 dbt v1.0.0 Compatibility 🎉

🚨 Breaking Changes 🚨

• Adjusts the require-dbt-version to now be within the range [">=1.0.0", "<2.0.0"]. Additionally, the package has been updated for dbt v1.0.0 compatibility. If you are using a dbt version <1.0.0, you will need to upgrade in order to leverage the latest version of the package.
  • For help upgrading your package, I recommend reviewing this GitHub repo's Release Notes on what changes have been implemented since your last upgrade.
  • For help upgrading your dbt project to dbt v1.0.0, I recommend reviewing dbt-labs upgrading to 1.0.0 docs for more details on what changes must be made.
• Upgrades the package dependency to refer to the latest dbt_fivetran_utils. The latest dbt_fivetran_utils package also has a dependency on dbt_utils [">=0.8.0", "<0.9.0"].
  • Please note, if you are installing a version of dbt_utils in your packages.yml that is not in the range above then you will encounter a package dependency error.