• Produces modeled tables that leverage Microsoft Ads data from Fivetran's connector in the format described by this ERD and builds off the output of our Microsoft Ads source package.
• Enables you to better understand the performance of your ads across varying grains:
  • Providing an account, campaign, ad group, keyword, ad, utm and search level reports.
• Materializes output models designed to work simultaneously with our multi-platform Ad Reporting package.
• Generates a comprehensive data dictionary of your source and modeled Microsoft Ads data through the dbt docs site.

The following table provides a detailed list of all tables materialized within this package by default.

TIP: See more details about these tables in the package's dbt docs site.

To use this dbt package, you must have the following:

• At least one Fivetran Microsoft Ads connector syncing data into your destination.
• A BigQuery, Snowflake, Redshift, PostgreSQL, or Databricks destination.

If you are using a Databricks destination with this package you will need to add the below (or a variation of the below) dispatch configuration within your dbt_project.yml. This is required in order for the package to accurately search for macros within the dbt-labs/spark_utils then the dbt-labs/dbt_utils packages respectively.

dispatch:
  - macro_namespace: dbt_utils
    search_order: ['spark_utils', 'dbt_utils']

If you are NOT using the Ad Reporting combination package, include the following microsoft_ads package version in your packages.yml file:

TIP: Check dbt Hub for the latest installation instructions or read the dbt docs for more information on installing packages.

packages:
  - package: fivetran/microsoft_ads
    version: [">=0.9.0", "<0.10.0"]

Do NOT include the microsoft_ads_source package in this file. The transformation package itself has a dependency on it and will install the source package as well.

By default, this package runs using your destination and the microsoft_ads schema. If this is not where your Microsoft Ads data is (for example, if your Microsoft Ads schema is named microsoft_ads_fivetran), add the following configuration to your root dbt_project.yml file:

vars:
    microsoft_ads_database: your_destination_name
    microsoft_ads_schema: your_schema_name 

vars:
    microsoft_ads_union_schemas: ['microsoft_ads_usa','microsoft_ads_canada'] # use this if the data is in different schemas/datasets of the same database/project
    microsoft_ads_union_databases: ['microsoft_ads_usa','microsoft_ads_canada'] # use this if the data is in different databases/projects but uses the same schema name

vars:
    microsoft_ads__account_passthrough_metrics: 
      - name: "new_custom_field"
        alias: "custom_field"
    microsoft_ads__campaign_passthrough_metrics:
      - name: "this_field"
    microsoft_ads__ad_group_passthrough_metrics:
      - name: "unique_string_field"
        alias: "field_id"
    microsoft_ads__ad_passthrough_metrics: #these metrics are included in both microsoft_ads__ad_report and microsoft_ads__url_report
      - name: "new_custom_field"
        alias: "custom_field"
      - name: "a_second_field"
    microsoft_ads__keyword_passthrough_metrics:
      - name: "this_field"
    microsoft_ads__search_passthrough_metrics:
      - name: "unique_string_field"
        alias: "field_id"

vars:
    microsoft_ads_auto_tagging_enabled: true # False by default

models:
    microsoft_ads_source:
       schema: my_new_schema_name # leave blank for just the target_schema
    microsoft_ads:
       schema: my_new_schema_name # leave blank for just the target_schema

vars:
    microsoft_ads_<default_source_table_name>_identifier: your_table_name 

This dbt package is dependent on the following dbt packages. These dependencies are installed by default within this package. For more information on the following packages, refer to the dbt hub site.

IMPORTANT: If you have any of these dependent packages in your own packages.yml file, we highly recommend that you remove them from your root packages.yml to avoid package version conflicts.

packages:
    - package: fivetran/microsoft_ads_source
      version: [">=0.10.0", "<0.11.0"]

    - package: fivetran/fivetran_utils
      version: [">=0.4.0", "<0.5.0"]

    - package: dbt-labs/dbt_utils
      version: [">=1.0.0", "<2.0.0"]

    - package: dbt-labs/spark_utils
      version: [">=0.3.0", "<0.4.0"]

The Fivetran team maintaining this package only maintains the latest version of the package. We highly recommend you stay consistent with the latest version of the package and refer to the CHANGELOG and release notes for more information on changes across versions.

In creating this package, which is meant for a wide range of use cases, we had to take opinionated stances on a few different questions we came across during development. We've consolidated significant choices we made in the DECISIONLOG.md, and will continue to update as the package evolves. We are always open to and encourage feedback on these choices, and the package in general.

A small team of analytics engineers at Fivetran develops these dbt packages. However, the packages are made better by community contributions.

We highly encourage and welcome contributions to this package. Check out this dbt Discourse article on the best workflow for contributing to a package.

We thank everyone who has taken the time to contribute. Each PR, bug report, and feature request has made this package better and is truly appreciated.

A special thank you to Seer Interactive, who we closely collaborated with to introduce native conversion support to our Ad packages.

• If you have questions or want to reach out for help, see the GitHub Issue section to find the right avenue of support for you.
• If you would like to provide feedback to the dbt package team at Fivetran or would like to request a new dbt package, fill out our Feedback Form.