Updated language and image (#6501)

dbt-labs · Nov 18, 2024 · 3a24380 · 3a24380
2 parents 8913c93 + 37af24e
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diff --git a/website/docs/docs/cloud/manage-access/set-up-sso-microsoft-entra-id.md b/website/docs/docs/cloud/manage-access/set-up-sso-microsoft-entra-id.md
@@ -120,8 +120,9 @@ To complete setup, follow the steps below in the dbt Cloud application.
 
 ### Supplying credentials
 
-25. Click the gear icon at the top right and select **Profile settings**. To the left, select **Single Sign On** under **Account Settings**.
-26. Click the **Edit** button and supply the following SSO details:
+25. From dbt Cloud, click on your account name in the left side menu and select **Account settings**.
+26. Click **Single sign-on** from the menu.
+27. Click the **Edit** button and supply the following SSO details:
 
 | Field | Value |
 | ----- | ----- |

diff --git a/website/docs/faqs/Project/dbt-source-freshness.md b/website/docs/faqs/Project/dbt-source-freshness.md
@@ -11,4 +11,4 @@ The `dbt source freshness` command will output a pass/warning/error status for e
 
 Additionally, dbt will write the freshness results to a file in the `target/` directory called `sources.json` by default. You can also override this destination, use the `-o` flag to the `dbt source freshness` command.
 
-After enabling source freshness within a job, configure [Artifacts](/docs/deploy/artifacts) in your **Project Details** page, which you can find by clicking the gear icon and then selecting **Account settings**. You can see the current status for source freshness by clicking **View Sources** in the job page.
+After enabling source freshness within a job, configure [Artifacts](/docs/deploy/artifacts) in your **Project Details** page, which you can find by selectng your account name on the left side menu in dbt Cloud and clicking **Account settings**. You can see the current status for source freshness by clicking **View Sources** in the job page.
diff --git a/website/docs/guides/dbt-python-snowpark.md b/website/docs/guides/dbt-python-snowpark.md
@@ -286,7 +286,7 @@ We need to obtain our data source by copying our Formula 1 data into Snowflake t
 
 ## Change development schema name navigate the IDE
 
-1. First we are going to change the name of our default schema to where our dbt models will build. By default, the name is `dbt_`. We will change this to `dbt_<YOUR_NAME>` to create your own personal development schema. To do this, select **Profile Settings** from the gear icon in the upper right.
+1. First we are going to change the name of our default schema to where our dbt models will build. By default, the name is `dbt_`. We will change this to `dbt_<YOUR_NAME>` to create your own personal development schema. To do this, click on your account name in the left side menu and select **Account settings**.
 
     <Lightbox src="/img/guides/dbt-ecosystem/dbt-python-snowpark/5-development-schema-name/1-settings-gear-icon.png" title="Settings menu"/>
 

diff --git a/website/docs/reference/dbt-jinja-functions/target.md b/website/docs/reference/dbt-jinja-functions/target.md
@@ -10,7 +10,7 @@ The `target` variable contains information about your connection to the warehous
 - **dbt Core:** These values are based on the target defined in your [profiles.yml](/docs/core/connect-data-platform/profiles.yml) file. Please note that for certain adapters, additional configuration steps may be required. Refer to the [set up page](/docs/core/connect-data-platform/about-core-connections) for your data platform.
 - **dbt Cloud** To learn more about setting up your adapter in dbt Cloud, refer to [About data platform connections](/docs/cloud/connect-data-platform/about-connections).
    - **[dbt Cloud Scheduler](/docs/deploy/job-scheduler)**: `target.name` is defined per job as described in [Custom target names](/docs/build/custom-target-names). For other attributes, values are defined by the deployment connection. To check these values, click **Deploy** and select **Environments**. Then, select the relevant deployment environment, and click **Settings**.
-   - **[dbt Cloud IDE](/docs/cloud/dbt-cloud-ide/develop-in-the-cloud)**: These values are defined by your connection and credentials. To edit these values, click the gear icon in the top right, select **Profile settings**, and click **Credentials**. Select and edit a project to set up the credentials and target name.
+   - **[dbt Cloud IDE](/docs/cloud/dbt-cloud-ide/develop-in-the-cloud)**: These values are defined by your connection and credentials. To edit these values, click on your account name in the left side menu and select **Account settings**. Then, click **Credentials**. Select and edit a project to set up the credentials and target name.
 
 Some configurations are shared between all adapters, while others are adapter-specific.
 

diff --git a/...cosystem/dbt-python-snowpark/5-development-schema-name/1-settings-gear-icon.png b/...cosystem/dbt-python-snowpark/5-development-schema-name/1-settings-gear-icon.png
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Expand Up		@@ -11,4 +11,4 @@ The `dbt source freshness` command will output a pass/warning/error status for e

		Additionally, dbt will write the freshness results to a file in the `target/` directory called `sources.json` by default. You can also override this destination, use the `-o` flag to the `dbt source freshness` command.

		After enabling source freshness within a job, configure [Artifacts](/docs/deploy/artifacts) in your Project Details page, which you can find by clicking the gear icon and then selecting Account settings. You can see the current status for source freshness by clicking View Sources in the job page.
		After enabling source freshness within a job, configure [Artifacts](/docs/deploy/artifacts) in your Project Details page, which you can find by selectng your account name on the left side menu in dbt Cloud and clicking Account settings. You can see the current status for source freshness by clicking View Sources in the job page.