fivetran · fivetran-sheringuyen · Sep 1, 2022 · Jul 5, 2022 · Jul 5, 2022 · Jul 5, 2022
diff --git a/.circleci/config.yml b/.circleci/config.yml
@@ -32,16 +32,6 @@ jobs:
             dbt seed --target postgres --full-refresh
             dbt run --target postgres --full-refresh
             dbt test --target postgres
-      - run:
-          name: "Run Tests - Spark"
-          command: |
-            . venv/bin/activate
-            echo `pwd`
-            cd integration_tests
-            dbt deps
-            dbt seed --target spark --full-refresh
-            dbt run --target spark --full-refresh
-            dbt test --target spark
       - run:
           name: "Run Tests - Redshift"
           command: |
@@ -74,4 +64,14 @@ jobs:
             dbt deps
             dbt seed --target bigquery --full-refresh
             dbt run --target bigquery --full-refresh
-            dbt test --target bigquery
+            dbt test --target bigquery
+      - run:
+          name: "Run Tests - Spark"
+          command: |
+            . venv/bin/activate
+            echo `pwd`
+            cd integration_tests
+            dbt deps
+            dbt seed --target spark --full-refresh
+            dbt run --target spark --full-refresh
+            dbt test --target spark
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,3 +1,52 @@
+# dbt_microsoft_ads_source v0.6.0
+
+## 🚨 Breaking Changes 🚨
+[PR #20](https://github.com/fivetran/dbt_microsoft_ads_source/pull/20) makes the below updates that may affect your workflow:
+- `modified_timestamp` columns have been renamed to `modified_at` and `is_most_recent_version` has been renamed to `is_most_recent_record` to reflect more recent package coding standards for the below models:
+  - `stg_microsoft_ads__account_history`
+  - `stg_microsoft_ads__ad_group_history`
+  - `stg_microsoft_ads__ad_history`
+  - `stg_microsoft_ads__ad_performance_daily_report`
+  - `stg_microsoft_ads__campaign_history`
+- Deprecating `*_version_id` fields in `*_history` models.
+
+## 🎉 Feature Enhancements 🎉
+We have added the below feature enhancements to this package in [PR #20](https://github.com/fivetran/dbt_microsoft_ads_source/pull/20):
+- Add `get_*_columns` macros for previously included models and newly added models.
+- Updated staging model standards on old models to conform with recent package development standards. Updates were made to the below models:
+  - `stg_microsoft_ads__account_history`
+  - `stg_microsoft_ads__ad_group_history`
+  - `stg_microsoft_ads__ad_history`
+  - `stg_microsoft_ads__ad_performance_daily_report`
+  - `stg_microsoft_ads__campaign_history`
+- New history and daily performance staging models including:
+  - `stg_microsoft_ads__account_daily_report` 
+  - `stg_microsoft_ads__campaign_daily_report` 
+  - `stg_microsoft_ads__ad_group_daily_report` 
+  - `stg_microsoft_ads__search_daily_report`
+  - `stg_microsoft_ads__keyword_daily_report`
+  - `stg_microsoft_ads__keyword_history`
+- `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.
+- More robust testing for better data integrity including: 
+  - Freshness tests
+  - Model grain tests
+- Inclusion of passthrough metrics:
+  - `microsoft_ads__account_passthrough_metrics`
+  - `microsoft_ads__campaign_passthrough_metrics`
+  - `microsoft_ads__ad_group_passthrough_metrics`
+  - `microsoft_ads__ad_passthrough_metrics`
+  - `microsoft_ads__keyword_passthrough_metrics`
+  - `microsoft_ads__search_passthrough_metrics`
+> This applies to all passthrough columns within the `dbt_microsoft_ads_source` package and not just the `microsoft_ads__ad_passthrough_metrics` example.
+```yml
+vars:
+  microsoft_ads__ad_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.
+```
+- Additional documentation for new models added.
+
 # dbt_microsoft_ads_source v0.5.0
 
 ## 🚨 Breaking Changes 🚨

diff --git a/README.md b/README.md
@@ -1,87 +1,132 @@
-[![Apache License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
-# Microsoft Advertising (Source)
+<p align="center">
+    <a alt="License"
+        href="https://github.com/fivetran/dbt_microsoft_ads_source/blob/main/LICENSE">
+        <img src="https://img.shields.io/badge/License-Apache%202.0-blue.svg" /></a>
+    <a alt="dbt-core">
+        <img src="https://img.shields.io/badge/dbt_Core™_version->=1.0.0_<2.0.0-orange.svg" /></a>
+    <a alt="Maintained?">
+        <img src="https://img.shields.io/badge/Maintained%3F-yes-green.svg" /></a>
+    <a alt="PRs">
+        <img src="https://img.shields.io/badge/Contributions-welcome-blueviolet" /></a>
+</p>
+
+# Microsoft Ads Source dbt Package ([Docs](https://fivetran.github.io/dbt_microsoft_ads_source/))
+# 📣 What does this dbt package do?
+- Materializes [Microsoft Ads staging tables](https://fivetran.github.io/dbt_microsoft_ads_source/#!/overview/microsoft_ads_source/models/?g_v=1&g_e=seeds) which leverage data in the format described by [this ERD](https://fivetran.com/docs/applications/microsoft-advertising#schemainformation). These staging tables clean, test, and prepare your microsoft_ads data from [Fivetran's connector](https://fivetran.com/docs/applications/microsoft-advertising) for analysis by doing the following:
+  - Names columns for consistency across all packages and for easier analysis
+  - Adds freshness tests to source data
+  - Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
+- Generates a comprehensive data dictionary of your Microsoft Ads data through the [dbt docs site](https://fivetran.github.io/dbt_microsoft_ads_source/).
+- These tables are designed to work simultaneously with our [Microsoft Ads transformation package](https://github.com/fivetran/dbt_microsoft_ads).
+
+# 🎯 How do I use the dbt package?
+## Step 1: Prerequisites
+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.
 
-This package models Microsoft Advertising data from [Fivetran's connector](https://fivetran.com/docs/applications/microsoft-advertising). It uses data in the format described by [this ERD](https://fivetran.com/docs/applications/microsoft-advertising#schemainformation).
-
-This package enriches your Fivetran data by doing the following:
-
-* Adds descriptions to tables and columns that are synced using Fivetran
-* Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
-* Models staging tables, which will be used in our transform package
-
-## Models
-
-This package contains staging models, designed to work simultaneously with our [Microsoft Advertising transformation package](https://github.com/fivetran/dbt_microsoft_ads) and our [multi-platform Ad Reporting package](https://github.com/fivetran/dbt_ad_reporting). The staging models name columns consistently across all packages:
-* Boolean fields are prefixed with `is_` or `has_`
-* Timestamps are appended with `_at`
-* ID primary keys are prefixed with the name of the table. For example, the campaign table's ID column is renamed `campaign_id`.
-
-## Installation Instructions
-Check [dbt Hub](https://hub.getdbt.com/) for the latest installation instructions, or [read the dbt docs](https://docs.getdbt.com/docs/package-management) for more information on installing packages.
-
-Include in your `packages.yml`
+### Databricks Dispatch Configuration
+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.
+```yml
+dispatch:
+  - macro_namespace: dbt_utils
+    search_order: ['spark_utils', 'dbt_utils']
+```
 
+## Step 2: Install the package
+Include the following microsoft_ads_source package version in your `packages.yml` file.
+> TIP: Check [dbt Hub](https://hub.getdbt.com/) for the latest installation instructions or [read the dbt docs](https://docs.getdbt.com/docs/package-management) for more information on installing packages.
 ```yaml
 packages:
   - package: fivetran/microsoft_ads_source
-    version: [">=0.5.0", "<0.6.0"]
+    version: [">=0.6.0", "<0.7.0"]
 ```
-
-## Configuration
-By default, this package looks for your Microsoft Advertising data in the `bingads` schema of your [target database](https://docs.getdbt.com/docs/running-a-dbt-project/using-the-command-line-interface/configure-your-profile). If this is not where your Microsoft Advertising data is, add the following configuration to your `dbt_project.yml` file:
+## Step 3: Define database and schema variables
+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:
 
 ```yml
-# dbt_project.yml
-
-...
-config-version: 2
-
 vars:
-    microsoft_ads_schema: your_schema_name
-    microsoft_ads_database: your_database_name
+    microsoft_ads_database: your_destination_name
+    microsoft_ads_schema: your_schema_name 
 ```
 
-### Changing the Build Schema
-By default this package will build the Microsoft Ads staging models within a schema titled (<target_schema> + `_stg_microsoft_ads`) in your target database. If this is not where you would like your Microsoft Ads staging data to be written to, add the following configuration to your `dbt_project.yml` file:
+## (Optional) Step 4: Additional configurations
+<details><summary>Expand for configurations</summary>
+
+### Passing Through Additional Metrics
+By default, this package will select `clicks`, `impressions`, and `cost` from the source reporting tables to store into the staging models. If you would like to pass through additional metrics to the staging models, add the below configurations to your `dbt_project.yml` file. These variables allow for the pass-through fields to be aliased (`alias`) if desired, but not required. Use the below format for declaring the respective pass-through variables:
+
+>**Note** Please ensure you exercised due diligence when adding metrics to these models. The metrics added by default (taps, impressions, and spend) have been vetted by the Fivetran team maintaining this package for accuracy. There are metrics included within the source reports, for example metric averages, which may be inaccurately represented at the grain for reports created in this package. You will want to ensure whichever metrics you pass through are indeed appropriate to aggregate at the respective reporting levels provided in this package.
 
 ```yml
-# dbt_project.yml
+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: 
+      - 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"
+```
+### Change the build schema
+By default, this package builds the Microsoft Ads staging models within a schema titled (`<target_schema>` + `_microsoft_ads_source`) in your destination. If this is not where you would like your Microsoft Ads staging data to be written to, add the following configuration to your root `dbt_project.yml` file:
 
-...
+```yml
 models:
     microsoft_ads_source:
       +schema: my_new_schema_name # leave blank for just the target_schema
 ```
-## Database Support
+
+### Change the source table references
+If an individual source table has a different name than the package expects, add the table name as it appears in your destination to the respective variable:
+> IMPORTANT: See this project's [`dbt_project.yml`](https://github.com/fivetran/dbt_microsoft_ads_source/blob/main/dbt_project.yml) variable declarations to see the expected names.
+
+```yml
+vars:
+    microsoft_ads_<default_source_table_name>_identifier: your_table_name 
+```
 
-This package has been tested on BigQuery, Snowflake, Redshift, Postgres, and Databricks.
+</details>
 
-### Databricks Dispatch Configuration
-dbt `v0.20.0` introduced a new project-level dispatch configuration that enables an "override" setting for all dispatched macros. 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.
+## (Optional) Step 5: Orchestrate your models with Fivetran Transformations for dbt Core™
+<details><summary>Expand for more details</summary>
+
+Fivetran offers the ability for you to orchestrate your dbt project through [Fivetran Transformations for dbt Core™](https://fivetran.com/docs/transformations/dbt). Learn how to set up your project for orchestration through Fivetran in our [Transformations for dbt Core™ setup guides](https://fivetran.com/docs/transformations/dbt#setupguide).
+
+</details>
+
+# 🔍 Does this package have dependencies?
+This dbt package is dependent on the following dbt packages. Please be aware that these dependencies are installed by default within this package. For more information on the following packages, refer to the [dbt hub](https://hub.getdbt.com/) 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.
 ```yml
-# dbt_project.yml
+packages:
+    - package: fivetran/fivetran_utils
+      version: [">=0.3.0", "<0.4.0"]
 
-dispatch:
-  - macro_namespace: dbt_utils
-    search_order: ['spark_utils', 'dbt_utils']
+    - package: dbt-labs/dbt_utils
+      version: [">=0.8.0", "<0.9.0"]
 ```
+
+# 🙌 How is this package maintained and can I contribute?
+## Package Maintenance
+The Fivetran team maintaining this package _only_ maintains the latest version of the package. We highly recommend that you stay consistent with the [latest version](https://hub.getdbt.com/fivetran/microsoft_ads_source/latest/) of the package and refer to the [CHANGELOG](https://github.com/fivetran/dbt_microsoft_ads_source/blob/main/CHANGELOG.md) and release notes for more information on changes across versions.
 
 ## Contributions
+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](https://discourse.getdbt.com/t/contributing-to-a-dbt-package/657) to learn how to contribute to a dbt package!
 
-Additional contributions to this package are very welcome! Please create issues
-or open PRs against `main`. Check out 
-[this post](https://discourse.getdbt.com/t/contributing-to-a-dbt-package/657) 
-on the best workflow for contributing to a package.
-
-## Resources:
-- Provide [feedback](https://www.surveymonkey.com/r/DQ7K7WW) on our existing dbt packages or what you'd like to see next
-- Have questions or feedback, or need help? Book a time during our office hours [here](https://calendly.com/fivetran-solutions-team/fivetran-solutions-team-office-hours) or shoot us an email at [email protected].
-- Find all of Fivetran's pre-built dbt packages in our [dbt hub](https://hub.getdbt.com/fivetran/)
-- Learn how to orchestrate your models with [Fivetran Transformations for dbt Core™](https://fivetran.com/docs/transformations/dbt)
-- Learn more about Fivetran overall [in our docs](https://fivetran.com/docs)
-- Check out [Fivetran's blog](https://fivetran.com/blog)
-- Learn more about dbt [in the dbt docs](https://docs.getdbt.com/docs/introduction)
-- Check out [Discourse](https://discourse.getdbt.com/) for commonly asked questions and answers
-- Join the [chat](http://slack.getdbt.com/) on Slack for live discussions and support
-- Find [dbt events](https://events.getdbt.com) near you
-- Check out [the dbt blog](https://blog.getdbt.com/) for the latest news on dbt's development and best practices
+# 🏪 Are there any resources available?
+- If you have questions or want to reach out for help, please refer to the [GitHub Issue](https://github.com/fivetran/dbt_microsoft_ads_source/issues/new/choose) 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](https://www.surveymonkey.com/r/DQ7K7WW).
+- Have questions or want to just say hi? Book a time during our office hours [on Calendly](https://calendly.com/fivetran-solutions-team/fivetran-solutions-team-office-hours) or email us at [email protected].
diff --git a/dbt_project.yml b/dbt_project.yml
@@ -1,15 +1,32 @@
 name: 'microsoft_ads_source'
-version: '0.5.0'
+version: '0.6.0'
 config-version: 2
 require-dbt-version: [">=1.0.0", "<2.0.0"]
-models:
-  microsoft_ads_source:
-    +schema: stg_microsoft_ads
-    +materialized: table
+
 vars:
   microsoft_ads_source:
     account_history: "{{ source('microsoft_ads','account_history') }}"
+    account_performance_daily_report: "{{ source('microsoft_ads', 'account_performance_daily_report') }}"
     ad_group_history: "{{ source('microsoft_ads','ad_group_history') }}"
+    ad_group_performance_daily_report: "{{ source('microsoft_ads', 'ad_group_performance_daily_report') }}"
     ad_history: "{{ source('microsoft_ads','ad_history') }}"
     ad_performance_daily_report: "{{ source('microsoft_ads','ad_performance_daily_report') }}"
     campaign_history: "{{ source('microsoft_ads','campaign_history') }}"
+    campaign_performance_daily_report: "{{ source('microsoft_ads', 'campaign_performance_daily_report') }}"
+    keyword_history: "{{ source('microsoft_ads','keyword_history') }}"
+    keyword_performance_daily_report: "{{ source('microsoft_ads', 'keyword_performance_daily_report') }}"
+    search_performance_daily_report: "{{ source('microsoft_ads', 'search_query_performance_daily_report') }}"
+
+  microsoft_ads__account_passthrough_metrics: []
+  microsoft_ads__campaign_passthrough_metrics: []
+  microsoft_ads__ad_group_passthrough_metrics: []
+  microsoft_ads__ad_passthrough_metrics: []
+  microsoft_ads__keyword_passthrough_metrics: []
+  microsoft_ads__search_passthrough_metrics: []
+
+models:
+  microsoft_ads_source:
+    +schema: microsoft_ads_source
+    +materialized: table
+    tmp:
+      +materialized: view
diff --git a/docs/catalog.json b/docs/catalog.json
diff --git a/docs/index.html b/docs/index.html
diff --git a/docs/manifest.json b/docs/manifest.json