diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md
index 35f658d..f450926 100644
--- a/.github/pull_request_template.md
+++ b/.github/pull_request_template.md
@@ -1,4 +1,3 @@
-Pull Request
**Are you a current Fivetran customer?**
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 8b7f52f..47cd245 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,3 +1,38 @@
+# dbt_pinterest_source v0.6.0
+
+## 🚨 Breaking Changes 🚨
+- The `pin_promotion_report_pass_through_metric` variable has been renamed to `pinterest__pin_promotion_report_passthrough_metrics`. ([#18](https://github.com/fivetran/dbt_pinterest_source/pull/18))
+- 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 metrics in the following format: ([#18](https://github.com/fivetran/dbt_pinterest_source/pull/18))
+> This applies to all passthrough metrics within the `dbt_pinterest_source` package and not just the `pinterest__pin_promotion_report_passthrough_metrics` example.
+```yml
+vars:
+ pinterest__pin_promotion_report_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.
+```
+## 🎉 Feature Enhancements 🎉
+PR [#18](https://github.com/fivetran/dbt_pinterest_source/pull/18) includes the following changes:
+- Addition of the following staging models which pull from the source counterparts. The inclusion of the additional `_report` source tables is to generate a more accurate representation of the Pinterest Ads data. For example, not all Ad types are included within the `pin_promotion_report` table. Therefore, the addition of the further grain reports will allow for more flexibility and accurate Pinterest Ad reporting.
+ - `stg_pinterest_ads__ad_group_report`
+ - `stg_pinterest_ads__advertiser_report`
+ - `stg_pinterest_ads__campaign_report`
+ - `stg_pinterest_ads__keyword_report`
+ - `stg_pinterest_ads__advertiser_history`
+ - `stg_pinterest_ads__keyword_history`
+
+- Inclusion of additional passthrough metrics:
+ - `pinterest__ad_group_report_passthrough_metrics`
+ - `pinterest__campaign_report_passthrough_metrics`
+ - `pinterest__advertiser_report_passthrough_metrics`
+ - `pinterest__keyword_report_passthrough_metrics`
+
+- 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.
+- Included grain uniqueness tests for each staging table.
+
+## Contributors
+- [@bnealdefero](https://github.com/bnealdefero) ([#18](https://github.com/fivetran/dbt_pinterest_source/pull/18))
+
# dbt_pinterest_source v0.5.0
🎉 dbt v1.0.0 Compatibility 🎉
## 🚨 Breaking Changes 🚨
diff --git a/README.md b/README.md
index ee49130..f23edac 100644
--- a/README.md
+++ b/README.md
@@ -1,104 +1,128 @@
-[](https://opensource.org/licenses/Apache-2.0)
-# Pinterest Ads (Source)
+
+
+
+
+
+
+
+
+
+
+
+# Pinterest Ads Source dbt Package ([Docs](https://fivetran.github.io/dbt_pinterest_source/))
+# 📣 What does this dbt package do?
+- Materializes [Pinterest Ads staging tables](https://fivetran.github.io/dbt_pinterest_source/#!/overview/pinterest_source/models/?g_v=1&g_e=seeds) which leverage data in the format described by [this ERD](https://fivetran.com/docs/applications/pinterest-ads#schemainformation). These staging tables clean, test, and prepare your Pinterest Ads data from [Fivetran's connector](https://fivetran.com/docs/applications/pinterest-ads) for analysis by doing the following:
+ - Name 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 Pinterest data through the [dbt docs site](https://fivetran.github.io/dbt_pinterest_source/).
+- These tables are designed to work simultaneously with our [Pinterest Ads transformation package](https://github.com/fivetran/dbt_pinterest).
+
+# 🎯 How do I use the dbt package?
+## Step 1: Prerequisites
+To use this dbt package, you must have the following:
+- At least one Fivetran Pinterest Ads connector syncing data into your destination.
+- A **BigQuery**, **Snowflake**, **Redshift**, **PostgreSQL**, or **Databricks** destination.
-This package models Pinterest Ads data from [Fivetran's connector](https://fivetran.com/docs/applications/pinterest-ads). It uses data in the format described by [this ERD](https://fivetran.com/docs/applications/pinterest-ads#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 [Pinterest Ads transformation package](https://github.com/fivetran/dbt_pinterest) 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 pinterest_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/pinterest_source
- version: [">=0.5.0", "<0.6.0"]
+ version: [">=0.6.0", "<0.7.0"]
```
-
-## Configuration
-By default, this package will look for your Pinterest Ads data in the `pinterest_ads` 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 Pinterest Ads data is, please 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 `pinterest` schema. If this is not where your Pinterest Ads data is (for example, if your pinterest schema is named `pinterest_fivetran`), add the following configuration to your root `dbt_project.yml` file:
```yml
-# dbt_project.yml
-
-...
-config-version: 2
-
vars:
- pinterest_database: your_database_name
+ pinterest_database: your_destination_name
pinterest_schema: your_schema_name
```
-### Passthrough Columns
-This package allows for custom columns not defined within the `stg_pinterest_ads__pin_promotion_report` model to be passed through. These custom columns may be applied using the `pin_promotion_report_pass_through_metric` variable. To apply custom passthrough columns use the below format:
+## (Optional) Step 4: Additional configurations
+Expand for configurations
-```yml
-# dbt_project.yml
+### 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:
-...
-vars:
- pin_promotion_report_pass_through_metric:
- - 'cool_new_field'
- - 'my_other_column'
- - 'pass_this_through_too'
+>**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
+vars:
+ pinterest__pin_promotion_report_passthrough_metrics:
+ - name: "new_custom_field"
+ alias: "custom_field"
+ pinterest__ad_group_report_passthrough_metrics:
+ - name: "this_field"
+ pinterest__advertiser_report_passthrough_metrics:
+ - name: "unique_string_field"
+ alias: "field_id"
+ pinterest__campaign_report_passthrough_metrics:
+ - name: "that_field"
+ pinterest__keyword_report_passthrough_metrics:
+ - name: "other_id"
+ alias: "another_id"
```
-
-### Changing the Build Schema
-By default this package will build the Pinterest Ads staging models within a schema titled ( + `_stg_pinterest`) in your target database. If this is not where you would like your Pinterest Ads staging data to be written to, add the following configuration to your `dbt_project.yml` file:
+### Change the build schema
+By default, this package builds the Pinterest Ads staging models within a schema titled (`` + `_pinterest_source`) in your destination. If this is not where you would like your pinterest staging data to be written to, add the following configuration to your root `dbt_project.yml` file:
```yml
-# dbt_project.yml
-
-...
models:
pinterest_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_pinterest_source/blob/main/dbt_project.yml) variable declarations to see the expected names.
+
+```yml
+vars:
+ pinterest__identifier: your_table_name
+```
-This package has been tested on BigQuery, Snowflake, Redshift, Postgres, and Databricks.
+ Expand for more details
+
+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).
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