Merge branch 'current' into mirnawong1-patch-28

dbt-labs · Jan 30, 2025 · 6c693e3 · 6c693e3
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diff --git a/website/blog/2022-05-03-making-dbt-cloud-api-calls-using-dbt-cloud-cli.md b/website/blog/2022-05-03-making-dbt-cloud-api-calls-using-dbt-cloud-cli.md
diff --git a/website/docs/docs/cloud/git/setup-azure-service-principal.md b/website/docs/docs/cloud/git/setup-azure-service-principal.md
@@ -44,7 +44,11 @@ A Microsoft Entra ID admin needs to perform the following steps:
 4. Provide a name for your app. We recommend using, "dbt Labs Azure DevOps app".
 5. Select **Accounts in any organizational directory (Any Entra ID directory - Multitenant)** as the Supported Account Types.
 Many customers ask why they need to select Multitenant instead of Single Tenant, and they frequently get this step wrong. Microsoft considers Azure DevOps (formerly called Visual Studio) and Microsoft Entra ID separate tenants, and for the Entra ID application to work properly, you must select Multitenant.
-6. Click **Register**.
+6. Set **Redirect URI (optional)** to **Web**. Copy and paste the Redirect URI from dbt Cloud into the next field.  To find the Redirect URI in dbt Cloud:
+    1. In dbt Cloud, navigate to **Account Settings** -> **Integrations**.
+    2. Click the **edit icon** next to **Azure DevOps**.
+    3. Copy the first **Redirect URIs** value which looks like `https://<YOUR_ACCESS_URL>/complete/azure_active_directory` and does NOT end with `service_user`.
+7. Click **Register**.
 
 Here's what your app should look like before registering it:
 

diff --git a/website/docs/docs/collaborate/column-level-lineage.md b/website/docs/docs/collaborate/column-level-lineage.md
@@ -3,6 +3,8 @@ title: "Column-level lineage"
 description: "Use dbt Explorer's column-level lineage to gain insights about your data at a granular level."
 ---
 
+# Column-level lineage <Lifecycle status='enterprise' />
+
 dbt Explorer now offers column-level lineage (CLL) for the resources in your dbt project. Analytics engineers can quickly and easily gain insight into the provenance of their data products at a more granular level. For each column in a resource (model, source, or snapshot) in a dbt project, Explorer provides end-to-end lineage for the data in that column given how it's used.
 
 CLL is available to dbt Cloud Enterprise accounts that can use Explorer. 

diff --git a/website/docs/docs/core/connect-data-platform/dremio-setup.md b/website/docs/docs/core/connect-data-platform/dremio-setup.md
@@ -37,7 +37,6 @@ Before connecting from project to Dremio Cloud, follow these prerequisite steps:
 * Ensure that you are using version 22.0 or later.
 * Ensure that Python 3.9.x or later is installed on the system that you are running dbt on.
 
-  See <a target="_blank" rel="noopener noreferrer" href="https://docs.dremio.com/software/advanced-administration/support-settings/#support-keys">Support Keys</a> in the Dremio documentation for the steps.
 * If you want to use TLS to secure the connection between dbt and Dremio Software, configure full wire encryption in your Dremio cluster. For instructions, see <a target="_blank" rel="noopener noreferrer" href="https://docs.dremio.com/software/deployment/wire-encryption-config/">Configuring Wire Encryption</a>.
 
 

diff --git a/website/docs/faqs/Troubleshooting/auth-expired-error.md b/website/docs/faqs/Troubleshooting/auth-expired-error.md
@@ -4,7 +4,7 @@ description: "Reauthenticate warehouse when seeing `authentication has expired`
 sidebar_label: 'Receiving `authentication has expired` error in the IDE'
 ---
 
-If you see a `authentication has expired` error when you try to run queries in the dbt CLoud IDE, this means your [OAuth](/docs/cloud/manage-access/set-up-snowflake-oauth) connection between Snowflake and dbt Cloud has expired.
+If you see a `authentication has expired` error when you try to run queries in the dbt Cloud IDE, this means your [OAuth](/docs/cloud/manage-access/set-up-snowflake-oauth) connection between Snowflake and dbt Cloud has expired.
 
 To fix this, you must reconnect the two tools.
 

diff --git a/website/docs/guides/sl-migration.md b/website/docs/guides/sl-migration.md
@@ -33,7 +33,7 @@ dbt Labs recommends completing these steps in a local dev environment (such as t
     ```bash
     python -m pip install "dbt-metricflow[snowflake]"
     ```
-    **Note** - MetricFlow commands aren't yet supported in the dbt CLoud IDE at this time.
+    **Note** - MetricFlow commands aren't yet supported in the dbt Cloud IDE at this time.
 
 2. Run `dbt parse`. This parses your project and creates a `semantic_manifest.json` file in your target directory. MetricFlow needs this file to query metrics. If you make changes to your configs, you will need to parse your project again. 
 3. Run `mf list metrics` to view the metrics in your project.

diff --git a/website/vercel.json b/website/vercel.json
@@ -2,6 +2,11 @@
   "cleanUrls": true,
   "trailingSlash": false,
   "redirects": [
+    {
+      "source": "/blog/making-dbt-cloud-api-calls-using-dbt-cloud-cli",
+      "destination": "/docs/dbt-cloud-apis/overview",
+      "permanent": true
+    },
     {
       "source": "/docs/cloud/git/setup-azure",
       "destination": "/docs/cloud/git/connect-azure-devops",