Skip to content

Latest commit

 

History

History
170 lines (142 loc) · 11 KB

CHANGELOG.md

File metadata and controls

170 lines (142 loc) · 11 KB
Raw

dbt_tiktok_ads v0.7.0

PR #22 includes the following updates:

Breaking Changes

  • Upstream Breaking Change: In the July 2023 TikTok Ads connector update for the ADGROUP_HISTORY table, the age column was renamed to age_groups.
    • This change primarily affects the upstream stg_tiktok_ads__ad_group_history model in dbt_tiktok_source. The age_groups column was not previously used in any downstream models within dbt_tiktok_ads, so this change impacts only the upstream staging model.
    • Previously, we coalesced the age and age_groups columns in the stg_tiktok_ads__ad_group_history model to accommodate connectors using the old naming convention. However, due to inconsistent data types, this approach is no longer viable.
    • As a result, the coalesced field has been removed in favor of the age_groups column.
    • If necessary, you can populate historical data in the age_groups column by performing a resync of the ADGROUP_HISTORY table, as TikTok provides all data regardless of the previous sync state.
    • For more details, see the DECISIONLOG entry.

Documentation

  • Added DECISIONLOG file:
    • Detailed the removal of the previously mentioned coalesced age and age_groups column.
    • Clarified why aggregation differences occur across varying grains.

dbt_tiktok_ads v0.6.0

PR #20 includes the following BREAKING CHANGE updates:

Feature Updates: Conversion Support

  • We have added the following source fields to each tiktok_ads end model (note that the conversion field was already present):

    • real_time_conversion: Number of times your ad resulted in the optimization event and timeframe you selected.
    • total_purchase_value: The total value of purchase events that occurred in your app that were recorded by your measurement partner.
    • total_sales_lead_value: The monetary worth or potential value assigned to a lead generated through ads.
    • total_conversion_value: The accumulated value of total_purchase_value and total_sales_lead_value.

  • In the event that you were already passing the above fields in via our passthrough columns, the package will dynamically avoid "duplicate column" errors.

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

Under the Hood

  • Created tiktok_ads_persist_pass_through_columns macro to ensure that the new conversion fields are backwards compatible with users who have already included them via passthrough fields.
  • Updated conversion field to be an integer rather than a numeric data type in the tiktok_ads_source package, as is the expected behavior of the field. This is a breaking change.
  • Added integrity and consistency validation tests within integration_tests folder for the transformation models (to be used by maintainers only).
  • Updated seed data to adequately test new field additions in integration tests.

Contributors

dbt_tiktok_ads v0.5.0

PR #13 includes the following updates:

Breaking changes

  • Updated the source identifier format for consistency with other packages and for compatibility with the fivetran_utils.union_data macro. Identifiers now are:
current previous
tiktok_ads_adgroup_history_identifier tiktok_ads__ad_group_history_identifier
tiktok_ads_ad_history_identifier tiktok_ads__ad_history_identifier
tiktok_ads_advertiser_identifier tiktok_ads__advertiser_identifier
tiktok_ads_campaign_history_identifier tiktok_ads__campaign_history_identifier
tiktok_ads_ad_report_hourly_identifier tiktok_ads__ad_report_hourly_identifier
tiktok_ads_adgroup_report_hourly_identifier tiktok_ads__ad_group_report_hourly_identifier
tiktok_ads_campaign_report_hourly_identifier tiktok_ads__campaign_report_hourly_identifier
  • If you are using the previous identifier, be sure to update to the current version!

Feature update 🎉

Under the hood 🚘

  • In the source package, 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 and downstream model and applied the fivetran_utils.source_relation macro.
    • The source_relation column is included in all joins in the transform package.
  • Updated tests to account for the new source_relation column.

dbt_tiktok_ads v0.4.0

PR #11 includes the following changes:

🚨 Breaking Changes 🚨

Updated model Removed fields
tiktok_ads__ad_group_report action_categories, age, languages, interest_category
tiktok_ads__ad_report action_categories, age, languages, interest_category
tiktok_ads__url_report action_categories, age, languages, interest_category

Note: All of the above fields were also removed due to complications with the BigQuery JSON datatype causing errors during compilation.

🔧 Under the Hood 🔩

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

dbt_tiktok_ads v0.3.0

🚨 Breaking Changes 🚨:

PR #7 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"].

🎉 Features 🎉

🚘 Under the Hood 🚘

  • Disabled the not_null test for tiktok_ads__url_report when null urls are allowed. PR #8

dbt_tiktok_ads v0.2.1

This PR (#6) updates the source package version.

dbt_tiktok_ads v0.2.0

This PR (#5) applies the following updates to provide further flexibility in your ad reporting. Additionally, these new end models will be leveraged in the respective downstream dbt_ad_reporting models.

🚨 Breaking Changes 🚨

  • Updates ad_group_hourly variable to ad_group_report_hourly
  • Removes intermediate models and instead incorporates previous logic into end models
  • Renames the tikok_ads__ad_adapter model to tiktok_ads__url_report
  • Removes dependency of models on the tikok_ads__ad_adapter model and moves that previous logic into each model, using corresponding hourly reports for each model's granularity (e.g. tikok_ads__campaign_report now uses the campaign_report_hourly)

🎉 Feature Enhancements 🎉

  • Adds in the following models and respective field descriptions and tests:
    • tiktok_ads__account_report
    • tiktok_ads__url_report
    • tiktok_ads__ad_report
  • Adds additional fields to existing models ad_group_report and campaign_report that were previously not brought in
  • Inclusion of passthrough metrics:
    • tiktok_ads__ad_group_hourly_passthrough_metrics
    • tiktok_ads__ad_hourly_passthrough_metrics
    • tiktok_ads__campaign_hourly_passthrough_metrics

This applies to all passthrough columns within the dbt_tiktok_ads package and not just the tiktok_ads__ad_group_hourly_passthrough_metrics example.

vars:
  tiktok_ads__ad_group_hourly_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.
  • Adds not-null tests to key fields
  • Applies standardization updates
  • Add enable configs for this specific ad platform, for use in the Ad Reporting rollup package

dbt_tiktok_ads v0.1.1

Under the Hood

  • Updated package yml to point to live source

dbt_tiktok_ads v0.1.0

Initial Release

  • This is the initial release of this package. For more information refer to the README.

Under the Hood

  • Aggregating daily metrics: As best practice, we try using the most granular data to perform aggregations. Therefore metrics such as spend and daily_cpc for each day is aggregated using the hourly source tables rather than daily source tables. In addition, aggregations done per ad group and per campaign is done using the ad table.