Merge branch 'current' into mirnawong1-patch-5

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diff --git a/website/docs/docs/cloud/manage-access/cloud-seats-and-users.md b/website/docs/docs/cloud/manage-access/cloud-seats-and-users.md
@@ -102,10 +102,10 @@ To delete a user in dbt Cloud, you must be an account owner or have admin privil
 If you are on a **Teams** plan and you're deleting users to reduce the number of billable seats, follow these steps to lower the license count to avoid being overcharged:
 
 1. In **Account Settings**, select **Billing**. 
-2. Enter the number of developer seats you want and make sure you fill in all the payment details, including the **Billing Address** section. Leaving these blank won't allow you to save your changes.
-3. Press **Update Payment Information** to save your changes. 
+2. Enter the number of developer seats you want and make sure you fill in all the payment details, including the **Billing Address** section. If you leave any field blank, you won't be able to save your changes.
+3. Click **Update Payment Information** to save your changes. 
 
-<Lightbox src="/img/docs/dbt-cloud/change-developer-seats.png" width="85%" title="Developer seats" />
+<Lightbox src="/img/docs/dbt-cloud/faq-account-settings-billing.jpg" width="85%" title="The **Billing** page in your **Account Settings**" />
 
 Great work! After completing these steps, your dbt Cloud user count and billing count should now be the same.
 

diff --git a/website/docs/faqs/Accounts/delete-users.md b/website/docs/faqs/Accounts/delete-users.md
@@ -10,19 +10,20 @@ To delete a user in dbt Cloud, you must be an account owner or have admin privil
 
 1. From dbt Cloud, click the gear icon at the top right and select **Account Settings**.
 
-<Lightbox src="/img/docs/dbt-cloud/Navigate To Account Settings.png" title="Navigate to account settings" />
+<Lightbox src="/img/docs/dbt-cloud/Navigate To Account Settings.png" width="85%"  title="Navigate to account settings" />
 
 2. In **Account Settings**, select **Users** under **Teams**.
 3. Select the user you want to delete, then click **Edit**. 
 4. Click **Delete** in the bottom left. Click **Confirm Delete** to immediately delete the user without additional password prompts. This action cannot be undone. However, you can re-invite the user with the same information if the deletion was made in error. 
 
-<Lightbox src="/img/docs/dbt-cloud/delete_user_20221023.gif" title="Deleting a user" />
+<Lightbox src="/img/docs/dbt-cloud/delete_user_20221023.gif" width="85%" title="Deleting a user" />
 
 If you are on a **Teams** plan and you are deleting users to reduce the number of billable seats, you also need to take these steps to lower the license count:
 1. In **Account Settings**, select **Billing**. 
-2. Enter the number of developer seats you want and click **Save**.
+2. Enter the number of developer seats you want and make sure you fill in all the payment details, including the **Billing Address** section. If you leave any field blank, you won't be able to save your changes.
+3. Click **Update Payment Information** to save your changes. 
 
-<Lightbox src="/img/docs/dbt-cloud/change-developer-seats.png" title="Developer seats" />
+<Lightbox src="/img/docs/dbt-cloud/faq-account-settings-billing.jpg" width="85%" title="Navigate to Account Settings -> Users to modify dbt Cloud users" />
 
 ## Related docs
 

diff --git a/website/docs/faqs/Project/example-projects.md b/website/docs/faqs/Project/example-projects.md
@@ -14,5 +14,6 @@ Yes!
 * **Attribution Playbook:** A demonstration project that models marketing attribution  ([source code](https://github.com/dbt-labs/attribution-playbook), [docs](https://www.getdbt.com/attribution-playbook/#!/overview))
 * **GitLab:** Gitlab's internal dbt project is open source and is a great example of how to use dbt at scale ([source code](https://gitlab.com/gitlab-data/analytics/-/tree/master/transform/snowflake-dbt), [docs](https://dbt.gitlabdata.com/))
 * **dummy-dbt:** A containerized dbt project that populates the Sakila database in Postgres and populates dbt seeds, models, snapshots, and tests. The project can be used for testing and experimentation purposes ([source code](https://github.com/gmyrianthous/dbt-dummy))
+* **Google Analytics 4:** A demonstration project that transforms the Google Analytics 4 BigQuery exports to various models ([source code](https://github.com/stacktonic-com/stacktonic-dbt-example-project), [docs](https://stacktonic.com/article/google-analytics-big-query-and-dbt-a-dbt-example-project))
 
 If you have an example project to add to this list, suggest an edit by clicking **Edit this page** below.
diff --git a/website/docs/guides/best-practices/how-we-structure/1-guide-overview.md b/website/docs/guides/best-practices/how-we-structure/1-guide-overview.md
@@ -52,7 +52,7 @@ We'll walk through our topics in the same order that our data would move through
 2. Explore how these layers fit into the rest of the project:
     1. Review the overall structure comprehensively
     2. Expand on YAML configuration in-depth
-    3. Discuss how to use the other folders in a dbt project: `tests`, `seeds`, and `analysis`
+    3. Discuss how to use the other folders in a dbt project: `tests`, `seeds`, and `analyses`
 
 Below is the complete file tree of the project we’ll be working through. Don’t worry if this looks like a lot of information to take in at once - this is just to give you the full vision of what we’re building towards. We’ll focus in on each of the sections one by one as we break down the project’s structure.
 

diff --git a/website/docs/guides/best-practices/how-we-structure/5-the-rest-of-the-project.md b/website/docs/guides/best-practices/how-we-structure/5-the-rest-of-the-project.md
@@ -80,7 +80,7 @@ One of the many benefits this consistent approach to project structure confers t
 
 ```yaml
 jaffle_shop
-├── analysis
+├── analyses
 ├── seeds
 │   └── employees.csv
 ├── macros
@@ -95,7 +95,7 @@ We’ve focused heavily thus far on the primary area of action in our dbt projec
 
 - ✅ `seeds` for lookup tables. The most common use case for seeds is loading lookup tables that are helpful for modeling but don’t exist in any source systems — think mapping zip codes to states, or UTM parameters to marketing campaigns. In this example project we have a small seed that maps our employees to their `customer_id`s, so that we can handle their purchases with special logic.
 - ❌ `seeds` for loading source data. Do not use seeds to load data from a source system into your warehouse. If it exists in a system you have access to, you should be loading it with a proper EL tool into the raw data area of your warehouse. dbt is designed to operate on data in the warehouse, not as a data-loading tool.
-- ✅ `analysis` for storing auditing queries. The `analysis` folder lets you store any queries you want to use Jinja with and version control, but not build into models in your warehouse. There are limitless possibilities here, but the most common use case when we set up projects at dbt Labs is to keep queries that leverage the [audit helper](https://github.com/dbt-labs/dbt-audit-helper) package. This package is incredibly useful for finding discrepancies in output when migrating logic from another system into dbt.
+- ✅ `analyses` for storing auditing queries. The `analyses` folder lets you store any queries you want to use Jinja with and version control, but not build into models in your warehouse. There are limitless possibilities here, but the most common use case when we set up projects at dbt Labs is to keep queries that leverage the [audit helper](https://github.com/dbt-labs/dbt-audit-helper) package. This package is incredibly useful for finding discrepancies in output when migrating logic from another system into dbt.
 - ✅ `tests` for testing multiple specific tables simultaneously. As dbt tests have evolved, writing singular tests has become less and less necessary. It's extremely useful for work-shopping test logic, but more often than not you'll find yourself either migrating that logic into your own custom generic tests or discovering a pre-built test that meets your needs from the ever-expanding universe of dbt packages (between the extra tests in [`dbt-utils`](https://github.com/dbt-labs/dbt-utils) and [`dbt-expectations`](https://github.com/calogica/dbt-expectations) almost any situation is covered). One area where singular tests still shine though is flexibly testing things that require a variety of specific models. If you're familiar with the difference between [unit tests](https://en.wikipedia.org/wiki/Unit_testing) [and](https://www.testim.io/blog/unit-test-vs-integration-test/) [integration](https://www.codecademy.com/resources/blog/what-is-integration-testing/) [tests](https://en.wikipedia.org/wiki/Integration_testing) in software engineering, you can think of generic and singular tests in a similar way. If you need to test the results of how several specific models interact or relate to each other, a singular test will likely be the quickest way to nail down your logic.
 - ✅ `snapshots` for creating [Type 2 slowly changing dimension](https://en.wikipedia.org/wiki/Slowly_changing_dimension#Type_2:_add_new_row) records from [Type 1](https://en.wikipedia.org/wiki/Slowly_changing_dimension#Type_1:_overwrite) (destructively updated) source data. This is [covered thoroughly in the dbt Docs](/docs/build/snapshots), unlike these other folders has a more defined purpose, and is out-of-scope for this guide, but mentioned for completion.
 - ✅ `macros` for DRY-ing up transformations you find yourself doing repeatedly. Like snapshots, a full dive into macros is out-of-scope for this guide and well [covered elsewhere](/docs/build/jinja-macros), but one important structure-related recommendation is to [write documentation for your macros](https://docs.getdbt.com/faqs/docs/documenting-macros). We recommend creating a `_macros.yml` and documenting the purpose and arguments for your macros once they’re ready for use.

diff --git a/website/static/img/docs/dbt-cloud/change-developer-seats.png b/website/static/img/docs/dbt-cloud/change-developer-seats.png
diff --git a/website/static/img/docs/dbt-cloud/faq-account-settings-billing.jpg b/website/static/img/docs/dbt-cloud/faq-account-settings-billing.jpg