Fix SQL statements, add claryfing comments in the Teradata quickstart

website/docs/guides/teradata-qs.md

@@ -75,7 +75,7 @@
         email varchar (100)
     )
     USING (
-        LOCATION ('/gs/storage.googleapis.com/clearscape_analytics_demo_data/dbt/rawcustomers.csv')
+        LOCATION ('/gs/storage.googleapis.com/clearscape_analytics_demo_data/dbt/raw_customers.csv')
     )
     NO PRIMARY INDEX;
 
@@ -137,7 +137,43 @@
 
 ## Delete the example models
 
-<Snippet path="quickstarts/delete-example-models" />
+You can now delete the files that dbt created when you initialized the project:
+
+1. Delete the `models/example/` directory.
+2. Delete the `example:` key from your `dbt_project.yml` file, and any configurations that are listed under it.
+
+    <File name='dbt_project.yml'>
+
+    ```yaml
+    # before
+    models:
+      my_new_project:
+        +materialized: table
+        example:
+          +materialized: view
+    ```
+
+    </File>
+
+    <File name='dbt_project.yml'>
+
+    ```yaml
+    # after
+    models:
+      my_new_project:
+        +materialized: table
+    ```
+
+    </File>
+
+3. Save your changes.
+4. Commit your changes and merge to the main branch.
+
+#### FAQs
+
+<FAQ path="Models/removing-deleted-models" />
+<FAQ path="Troubleshooting/unused-model-configurations" />
+
 
 ## Build your first model
 
@@ -239,8 +275,6 @@
       models:
         jaffle_shop:
           +materialized: table
-          example:
-            +materialized: view
       ```
 
       </File>
@@ -359,7 +393,7 @@
 
       from customers
 
-      left join customer_orders using (customer_id)
+      left join customer_orders on customers.customer_id = customer_orders.customer_id
 
    )
 
@@ -448,7 +482,136 @@
 
 </div>
 
-<Snippet path="quickstarts/test-and-document-your-project" />
+## Add tests to your models
+
+Adding [tests](/docs/build/data-tests) to a project helps validate that your models are working correctly.
+
+To add tests to your project:
+
+1. Create a new YAML file in the `models` directory, named `models/schema.yml`
+2. Add the following contents to the file:
+
+    <File name='models/schema.yml'>
+
+    ```yaml
+    version: 2
+
+    models:
+      - name: bi_customers
+        columns:
+          - name: customer_id
+            tests:
+              - unique
+              - not_null
+
+      - name: stg_customers
+        columns:
+          - name: customer_id
+            tests:
+              - unique
+              - not_null
+
+      - name: stg_orders
+        columns:
+          - name: order_id
+            tests:
+              - unique
+              - not_null
+          - name: status
+            tests:
+              - accepted_values:
+                  values: ['placed', 'shipped', 'completed', 'return_pending', 'returned']
+          - name: customer_id
+            tests:
+              - not_null
+              - relationships:
+                  to: ref('stg_customers')
+                  field: customer_id
+
+    ```
+
+    </File>
+
+3. Run `dbt test`, and confirm that all your tests passed.
+
+When you run `dbt test`, dbt iterates through your YAML files, and constructs a query for each test. Each query will return the number of records that fail the test. If this number is 0, then the test is successful.
+
+#### FAQs
+
+<FAQ path="Tests/available-tests" alt_header="What tests are available for me to use in dbt? Can I add my own custom tests?" />
+<FAQ path="Tests/test-one-model" />
+<FAQ path="Runs/failed-tests" />
+<FAQ path="Project/schema-yml-name" alt_header="Does my test file need to be named `schema.yml`?" />
+<FAQ path="Project/why-version-2" />
+<FAQ path="Tests/recommended-tests" />
+<FAQ path="Tests/when-to-test" />
+
+
+## Document your models
+
+Adding [documentation](/docs/build/documentation) to your project allows you to describe your models in rich detail, and share that information with your team. Here, we're going to add some basic documentation to our project.
+
+1. Update your `models/schema.yml` file to include some descriptions, such as those below.
+
+    <File name='models/schema.yml'>
+
+    ```yaml
+    version: 2
+
+    models:
+      - name: bi_customers
+        description: One record per customer
+        columns:
+          - name: customer_id
+            description: Primary key
+            tests:
+              - unique
+              - not_null
+          - name: first_order_date
+            description: NULL when a customer has not yet placed an order.
+
+      - name: stg_customers
+        description: This model cleans up customer data
+        columns:
+          - name: customer_id
+            description: Primary key
+            tests:
+              - unique
+              - not_null
+
+      - name: stg_orders
+        description: This model cleans up order data
+        columns:
+          - name: order_id
+            description: Primary key
+            tests:
+              - unique
+              - not_null
+          - name: status
+            tests:
+              - accepted_values:
+                  values: ['placed', 'shipped', 'completed', 'return_pending', 'returned']
+          - name: customer_id
+            tests:
+              - not_null
+              - relationships:
+                  to: ref('stg_customers')
+                  field: customer_id
+    ```
+
+    </File>
+
+2. Run `dbt docs generate` to generate the documentation for your project. dbt introspects your project and your warehouse to generate a <Term id="json" /> file with rich documentation about your project.
+
+
+3. Click the book icon in the Develop interface to launch documentation in a new tab.
+
+#### FAQs
+
+<FAQ path="Docs/long-descriptions" />
+<FAQ path="Docs/sharing-documentation" />
+
+
 
 ## Commit your changes
 
@@ -478,7 +641,7 @@
 2. Click **Create Environment**.
 3. In the **Name** field, write the name of your deployment environment. For example, "Production."
 4. In the **dbt Version** field, select the latest version from the dropdown.
-5. Under **Deployment connection**, enter the name of the dataset you want to use as the target, such as "Analytics". This will allow dbt to build and work with that dataset. For some data warehouses, the target dataset may be referred to as a "schema".
+5. Under **Deployment connection**, enter the name of the dataset you want to use as the target, such as `jaffle_shop_prod`. This will allow dbt to build and work with that dataset.
 6. Click **Save**.
 
 ### Create and run a job
@@ -488,7 +651,7 @@
 As the `jaffle_shop` business gains more customers, and those customers create more orders, you will see more records added to your source data. Because you materialized the `bi_customers` model as a table, you'll need to periodically rebuild your table to ensure that the data stays up-to-date. This update will happen when you run a job.
 
 1. After creating your deployment environment, you should be directed to the page for a new environment. If not, select **Deploy** in the upper left, then click **Jobs**.
-2. Click **Create one** and provide a name, for example, "Production run", and link to the Environment you just created.
+2. Click **+ Create job** and then select **Deploy job**. Provide a name, for example, "Production run", and link it to the Environment you just created.
 3. Scroll down to the **Execution Settings** section.
 4. Under **Commands**, add this command as part of your job if you don't see it:
    * `dbt build`