exports fast follows (#4873)

this pr adds the 'new' flag for the new exports doc and also adds the
link to the blog.

also refindes the config row in the saved queries and exports
comparison.

website/docs/docs/build/metrics-overview.md

@@ -40,7 +40,7 @@ metrics:
 
 This page explains the different supported metric types you can add to your dbt project.
 
-### Conversion metrics <Lifecycle status='new'/>
+### Conversion metrics
 
 [Conversion metrics](/docs/build/conversion) help you track when a base event and a subsequent conversion event occurs for an entity within a set time period.
 

website/docs/docs/build/saved-queries.md

@@ -18,7 +18,7 @@ Saved queries are distinct from [exports](/docs/use-dbt-semantic-layer/exports),
 | **Purpose**         | To materialize saved queries in your data platform and expose metrics and dimensions as a view or table. | To define and manage common Semantic Layer queries in YAML, which includes metrics and dimensions.   |
 | **Usage**           | Automatically runs saved queries and materializes them within your data platform. Exports count towards [queried metrics](/docs/cloud/billing#what-counts-as-a-queried-metric) usage. <br /><br />**Example**: Creating a weekly aggregated table for active user metrics, automatically updated and stored in the data platform.  | Used for organizing and reusing common MetricFlow queries within dbt projects.<br /><br /><br />**Example**: Group related metrics together for better organization, and include commonly uses dimensions and filters. | For materializing query results in the data platform. |
 | **Integration**     | Must have the dbt Semantic Layer configured in your dbt project.<br /><br />Tightly integrated with the [MetricFlow Server](/docs/use-dbt-semantic-layer/sl-architecture#components) and dbt Cloud's job scheduler. | Integrated into the dbt <Term id="dag" /> and managed alongside other dbt nodes. |
-| **Configuration**   | Configured within dbt Cloud environment and job scheduler settings. | Defined in YAML format within dbt project files.   |
+| **Configuration**   | Defined within the `saved_queries` configuration. Set up within the dbt Cloud environment and job scheduler settings. | Defined in YAML format within dbt project files.     |
 
 All metrics in a saved query need to use the same dimensions in the `group_by` or `where` clauses. The following is an example of a saved query:
 

website/docs/docs/dbt-versions/product-lifecycles.md

@@ -18,7 +18,7 @@ Any dbt feature will fall into one of the following lifecycle states:
 
 - **Preview (Private or Public):**  Preview features are stable and can be considered for production deployments. There may still be some planned additions and modifications to product behaviors before moving to General Availability. We may also introduce new functionality to Preview features that is not backward compatible. Preview features include documentation, technical support, and include service level objectives (SLOs). Features in Preview are generally provided at no extra cost, although they may become paid features in their Generally Available state.
 
-- **Generally Available(GA):** Generally Available features provide stable features that can be considered for production deployments. Service level agreements (SLAs) apply to GA features, and these features include documentation and technical support.
+- **Generally Available (GA):** Generally Available features provide stable features that can be considered for production deployments. Service level agreements (SLAs) apply to GA features, and these features include documentation and technical support.
 
 - **Deprecated:** Features in this state are not actively worked on or enhanced by dbt Labs and will continue to function as-is until their removal date. 
 

website/docs/docs/dbt-versions/release-notes/72-Feb-2024/exports-rn.md

@@ -11,6 +11,6 @@ You can now use the [exports](/docs/use-dbt-semantic-layer/exports) feature with
 
 By exposing tables of metrics and dimensions, exports enable you to integrate with additional tools that don't natively connect with the dbt Semantic Layer, such as PowerBI.
 
-Exports are available for dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) plans on dbt versions 1.7 or newer.
+Exports are available for dbt Cloud multi-tenant [Team or Enterprise](https://www.getdbt.com/pricing/) plans on dbt versions 1.7 or newer. Refer to the [exports blog](https://www.getdbt.com/blog/announcing-exports-for-the-dbt-semantic-layer) for more details.
 
 <Lightbox src="/img/docs/dbt-cloud/semantic-layer/deploy_exports.jpg" width="90%" title="Add an environment variable to run exports in your production run." />

website/docs/docs/use-dbt-semantic-layer/exports.md

@@ -4,18 +4,20 @@ description: "Use exports to materialize tables to the data platform on a schedu
 sidebar_label: "Materialize with exports"
 ---
 
+# Materialize queries with exports <Lifecycle status='new'/>
+
 The exports feature in the dbt Semantic Layer enhances the [saved queries](/docs/build/saved-queries) by allowing you to materialize commonly used queries directly within your data platform.
 
 While saved queries are a way to save and reuse commonly used queries in MetricFlow, exports take this functionality a step further by:
 
 - Enabling you to materialize these queries within your data platform using dbt Cloud.
 - Proving an integration path for tools that don't natively support the dbt Semantic Layer by exposing tables of metrics and dimensions.
 
-Essentially, exports are like any other table in your data platform. They enable you to query metric definitions through any SQL interface or connect to downstream tools without needing a first-class Semantic Layer integration. Refer to [Available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) for more information.
+Essentially, exports are like any other table in your data platform. They enable you to query metric definitions through any SQL interface or connect to downstream tools without a first-class Semantic Layer integration. Refer to [Available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) for more information.
 
 ## Prerequisites
 
-- You have a dbt Cloud account on a [Team or Enterprise](https://www.getdbt.com/pricing/) plan.
+- You have a multi-tenant dbt Cloud account on a [Team or Enterprise](https://www.getdbt.com/pricing/) plan. (Single-tenant is not supported at this time)
 - You are on [dbt version](/docs/dbt-versions/upgrade-core-in-cloud) 1.7 or newer.
 - You have the dbt Semantic Layer [configured](/docs/use-dbt-semantic-layer/setup-sl) in your dbt project.
 - You have a dbt Cloud environment with a [Job scheduler](/docs/deploy/job-scheduler) enabled.
@@ -29,7 +31,7 @@ Essentially, exports are like any other table in your data platform. They enable
 | **Purpose**         | To materialize saved queries in your data platform and expose metrics and dimensions as a view or table. | To define and manage common Semantic Layer queries in YAML, including metrics and dimensions.   |
 | **Usage**           | Automatically runs saved queries and materializes them within your data platform. Exports count towards [queried metrics](/docs/cloud/billing#what-counts-as-a-queried-metric) usage. <br /><br />Example: Create a weekly aggregated table for active user metrics, automatically updated and stored in the data platform.  | Used for organizing and reusing common MetricFlow queries within dbt projects.<br /><br /><br />Example: Group related metrics together for better organization, and include commonly used dimensions and filters. | For materializing query results in the data platform. |
 | **Integration**     | Must have the dbt Semantic Layer configured in your dbt project.<br /><br />Tightly integrated with the [MetricFlow Server](/docs/use-dbt-semantic-layer/sl-architecture#components) and dbt Cloud's job scheduler. | Integrated into the dbt <Term id="dag" /> and managed alongside other dbt nodes. |
-| **Configuration**   | Defined within the `saved_queries` configuration. Configured within the dbt Cloud environment and job scheduler settings. | Defined in YAML format within dbt project files.   |
+| **Configuration**   | Defined within the `saved_queries` configuration. Set up within the dbt Cloud environment and job scheduler settings. | Defined in YAML format within dbt project files.    |
 
 ## Define exports