[daggy-u- [dbt] - Minor corrections (#20103)

## Summary & Motivation

## How I Tested These Changes

---------

Co-authored-by: Tim Castillo <[email protected]>

docs/dagster-university/pages/dagster-dbt.md

@@ -34,6 +34,7 @@ title: Dagster + dbt
   - [Connecting dbt models to Dagster assets](/dagster-dbt/lesson-5/2-connecting-dbt-models-to-dagster-assets)
   - [Creating assets that depend on dbt models](/dagster-dbt/lesson-5/3-creating-assets-that-depend-on-dbt-models)
   - [Automating dbt models in Dagster](/dagster-dbt/lesson-5/4-automating-dbt-models-in-dagster)
+  - [Practice: Grouping dbt models by layer](/dagster-dbt/lesson-5/coding-practice-grouping-models)
 - Lesson 6: Using Dagster to partition dbt models
   - [Overview](/dagster-dbt/lesson-6/1-overview)
   - [Creating an incremental model](/dagster-dbt/lesson-6/2-creating-a-simple-incremental-model)

docs/dagster-university/pages/dagster-dbt/lesson-2/1-requirements.md

@@ -30,5 +30,5 @@ Even if you’ve already completed the Dagster Essentials course, you should sti
 Run the following to clone the project:
 
 ```bash
-git clone https://github.com/dagster-io/project-dagster-university -b module/dagster-and-dbt/starter
+git clone https://github.com/dagster-io/project-dagster-university -b module/dagster-and-dbt-starter
 ```

docs/dagster-university/pages/dagster-dbt/lesson-3/3-defining-the-dbt-project-location-in-dagster.md

@@ -21,6 +21,8 @@ The `Path` class from the `pathlib` standard library will help us create an accu
 DBT_DIRECTORY = Path(__file__).joinpath("..", "..", "..", "analytics").resolve()
 ```
 
+TODO: Tim to update as these instructions as the old instructions use `os.path.join`
+
 This line creates a new constant called `DBT_DIRECTORY`. This line might look a little complicated, so let’s break it down:
 
 - It uses `constants.py`'s file location (via `__file__`) as a point of reference for finding the dbt project

docs/dagster-university/pages/dagster-dbt/lesson-3/knowledge-check.md

@@ -20,8 +20,10 @@ lesson: '3'
 
 3. In the Dagster UI, re-materialize both of the dbt models.
 
-4. Navigate to the details page for the run you just started.
-
-5. Navigate to the logs for the run.
+4. Navigate to the details page for the run you just started, then look at the logs.
 
 When finished, proceed to the next page.
+
+{% callout %}
+> **Important!** Before continuing, change `dbt_analytics` back to use `dbt run`.
+{% /callout %}

docs/dagster-university/pages/dagster-dbt/lesson-5/coding-practice-grouping-models.md

@@ -0,0 +1,25 @@
+---
+title: 'Practice: Grouping dbt models by layer'
+module: 'dagster_essentials'
+lesson: '5'
+---
+
+# Practice: Grouping dbt models by layer
+
+Override the `get_group_name` method in your `CustomizedDagsterDbtTranslator` to group each dbt model by their layer (`marts` and `staging`).
+
+**Hint:** `dbt_resource_props`
+
+---
+
+## Check your work
+
+The method you built should look similar to the following code. Click **View answer** to view it.
+
+**If there are differences**, compare what you wrote to the code below and change them, as this method will be used as-is in future lessons.
+
+```python {% obfuscated="true" %}
+@classmethod
+def get_group_name(cls, dbt_resource_props):
+    return dbt_resource_props["fqn"][1]
+```

docs/dagster-university/pages/dagster-dbt/lesson-6/3-creating-a-partitioned-dbt-asset.md

@@ -154,11 +154,13 @@ Finally, we’ll modify the `daily_metrics.sql` file to reflect that dbt knows w
 
 In `analytics/models/marts/daily_metrics.sql`, update the model's incremental logic to the following:
 
+`{% if is_incremental() %}`
 ```python
-{% if is_incremental() %}
     where date_of_business >= strptime('{{ var('min_date') }}', '%c') and date_of_business < strptime('{{ var('max_date') }}', '%c')
-{% endif %}
 ```
+`{% endif %}`
+
+**TODO: AWARE THIS IS BROKEN - NEEDS A MARKDOC FIX**
 
 Here, we’ve changed the logic to say that we only want to select rows between the `min_date` and the `max_date`. Note that we are turning the variables into timestamps using `strptime` because they’re loaded as strings.
 

docs/dagster-university/pages/dagster-dbt/lesson-7/5-preparing-for-a-successful-run.md

@@ -121,6 +121,11 @@ The following table contains the environment variables we need to create in Dags
 - `AWS_REGION`
 - The region the S3 bucket is located in.
 
+---
+
+- `S3_BUCKET_NAME`
+- The name of the S3 bucket, by default `"s3://dagster-university/"`
+
 {% /table %}
 
 ### Creating environment variables