From 1def6ffcacc6655178f10021a13c11f1417b950a Mon Sep 17 00:00:00 2001
From: mirnawong1 <mirna.wong@fishtownanalytics.com>
Date: Mon, 5 Feb 2024 19:18:17 +0000
Subject: [PATCH] tweaks

---
 .../docs/docs/build/metricflow-commands.md    |  6 +--
 website/docs/docs/build/saved-queries.md      | 15 +++---
 .../docs/docs/dbt-cloud-apis/sl-graphql.md    | 10 ++--
 website/docs/docs/dbt-cloud-apis/sl-jdbc.md   |  6 +--
 .../release-notes/72-Feb-2024/exports-rn.md   | 16 ++++++
 .../73-Jan-2024/jan-sl-updates.md             |  2 +-
 .../docs/docs/deploy/deployment-overview.md   |  2 +-
 .../avail-sl-integrations.md                  | 10 ++--
 .../docs/use-dbt-semantic-layer/dbt-sl.md     |  2 +-
 .../docs/use-dbt-semantic-layer/exports.md    | 54 +++++++++++--------
 .../docs/use-dbt-semantic-layer/tableau.md    |  4 +-
 .../guides/sl-partner-integration-guide.md    |  6 +--
 website/snippets/_sl-connect-and-query-api.md |  4 +-
 13 files changed, 82 insertions(+), 55 deletions(-)
 create mode 100644 website/docs/docs/dbt-versions/release-notes/72-Feb-2024/exports-rn.md

diff --git a/website/docs/docs/build/metricflow-commands.md b/website/docs/docs/build/metricflow-commands.md
index b26b9c14139..b78d1033a04 100644
--- a/website/docs/docs/build/metricflow-commands.md
+++ b/website/docs/docs/build/metricflow-commands.md
@@ -75,7 +75,7 @@ You can use the `dbt sl` prefix before the command name to execute them in the d
 - [`list dimensions`](#list) &mdash; Lists unique dimensions for metrics.
 - [`list dimension-values`](#list-dimension-values) &mdash; List dimensions with metrics.
 - [`list entities`](#list-entities) &mdash; Lists all unique entities.
-- [`query`](#query) &mdash; Query metrics, saved queries, and dimensions you want to see in the command line interface. Refer to [query examples](#query-examples) to help you get started.
+- [`query`](#query) &mdash; Query metrics, Saved Queries, and dimensions you want to see in the command line interface. Refer to [query examples](#query-examples) to help you get started.
 
 <!--below commands aren't supported in dbt cloud yet
 - [`validate-configs`](#validate-configs) &mdash; Validates semantic model configurations.
@@ -437,8 +437,8 @@ mf query --saved-query <name> # In dbt Core
 
 For example, if you use dbt Cloud and have a saved query named `new_customer_orders`, you would run `dbt sl query --saved-query new_customer_orders`.
 
-:::info A note on querying saved queries
-When querying [saved queries](/docs/build/saved-queries),you can use parameters such as `where`, `limit`, `order`, `compile`, and so on. However, keep in mind that you can't access `metric` or `group_by` parameters in this context. This is because they are predetermined and fixed parameters for saved queries, and you can't change them at query time. If you would like to query more metrics or dimensions, you can build the query using the standard format.
+:::info A note on querying Saved Queries
+When querying [Saved Queries](/docs/build/saved-queries),you can use parameters such as `where`, `limit`, `order`, `compile`, and so on. However, keep in mind that you can't access `metric` or `group_by` parameters in this context. This is because they are predetermined and fixed parameters for Saved Queries, and you can't change them at query time. If you would like to query more metrics or dimensions, you can build the query using the standard format.
 :::
 
 </TabItem>
diff --git a/website/docs/docs/build/saved-queries.md b/website/docs/docs/build/saved-queries.md
index ee0fc6bb880..7b53657c93b 100644
--- a/website/docs/docs/build/saved-queries.md
+++ b/website/docs/docs/build/saved-queries.md
@@ -1,16 +1,16 @@
 ---
-title: Saved queries
+title: Saved Queries
 id: saved-queries
-description: "Saved queries are a way to save commonly used queries in MetricFlow. They can be used to save time and avoid writing the same query over and over again."
-sidebar_label: "Saved queries"
+description: "Saved Queries are a way to save commonly used queries in MetricFlow. They can be used to save time and avoid writing the same query over and over again."
+sidebar_label: "Saved Queries"
 tags: [Metrics, Semantic Layer]
 ---
 
-Saved queries are a way to save commonly used queries in MetricFlow. You can group metrics, dimensions, and filters that are logically related into a saved query. 
+Saved Queries are a way to save commonly used queries in MetricFlow. You can group metrics, dimensions, and filters that are logically related into a saved query. 
 
 ### Exports and Saved Queries comparison
 
-Saved queries are distinct from [Exports](/docs/use-dbt-semantic-layer/exports), which schedule and execute saved queries using [dbt Cloud's job scheduler](/docs/deploy/job-scheduler). The following table compares the features and usage of Exports and Saved Queries:
+Saved Queries are distinct from [Exports](/docs/use-dbt-semantic-layer/exports), which schedule and execute Saved Queries using [dbt Cloud's job scheduler](/docs/deploy/job-scheduler). The following table compares the features and usage of Exports and Saved Queries:
 
 | Feature |  Exports | <div style={{width:'250px, text-align: center'}}>Saved Queries</div>  |
 | ----------- | ----------- | ---------------- |
@@ -24,6 +24,8 @@ The following is an example of a saved query:
 
 All metrics in a saved query need to use the same dimensions in the `group_by` or `where` clauses.
 
+<File name='saved_queries.yml'>
+
 ```yaml
 saved_queries:
   - name: p0_booking
@@ -38,6 +40,7 @@ saved_queries:
       where:
         - "{{ Dimension('listing__capacity_latest') }} > 3"
 ```
+</File>
 
 ## Parameters
 
@@ -65,5 +68,3 @@ All metrics in a saved query need to use the same dimensions in the `group_by` o
 
 - [Exports](/docs/use-dbt-semantic-layer/exports)
 - [Set up the dbt Semantic Layer](/docs/use-dbt-semantic-layer/setup-sl)
-
-
diff --git a/website/docs/docs/dbt-cloud-apis/sl-graphql.md b/website/docs/docs/dbt-cloud-apis/sl-graphql.md
index e2a473b23e9..2bb72c07fa2 100644
--- a/website/docs/docs/dbt-cloud-apis/sl-graphql.md
+++ b/website/docs/docs/dbt-cloud-apis/sl-graphql.md
@@ -217,7 +217,7 @@ Dimension {
 DimensionType = [CATEGORICAL, TIME]
 ```
 
-**List saved queries**
+**List Saved Queries**
   
   ```graphql
   {
@@ -602,7 +602,7 @@ mutation {
 }
 ```
 
-**Querying compile SQL with saved queries** 
+**Querying compile SQL with Saved Queries** 
 
 This query includes the field `savedQuery` and generates the SQL based on a predefined [saved query](/docs/build/saved-queries),rather than dynamically building it from a list of metrics and groupings. You can use this for frequently used queries.
 
@@ -618,11 +618,11 @@ mutation {
 }
 ```
 
-:::info A note on querying saved queries
-When querying [saved queries](/docs/build/saved-queries),you can use parameters such as `where`, `limit`, `order`, `compile`, and so on. However, keep in mind that you can't access `metric` or `group_by` parameters in this context. This is because they are predetermined and fixed parameters for saved queries, and you can't change them at query time. If you would like to query more metrics or dimensions, you can build the query using the standard format.
+:::info A note on querying Saved Queries
+When querying [Saved Queries](/docs/build/saved-queries),you can use parameters such as `where`, `limit`, `order`, `compile`, and so on. However, keep in mind that you can't access `metric` or `group_by` parameters in this context. This is because they are predetermined and fixed parameters for Saved Queries, and you can't change them at query time. If you would like to query more metrics or dimensions, you can build the query using the standard format.
 :::
 
-**Create query with saved queries** 
+**Create query with Saved Queries** 
 
 This takes the same inputs as the `createQuery` mutation, but includes the field `savedQuery`. You can use this for frequently used queries.
 
diff --git a/website/docs/docs/dbt-cloud-apis/sl-jdbc.md b/website/docs/docs/dbt-cloud-apis/sl-jdbc.md
index 4727fcdbd21..d48340fc6d4 100644
--- a/website/docs/docs/dbt-cloud-apis/sl-jdbc.md
+++ b/website/docs/docs/dbt-cloud-apis/sl-jdbc.md
@@ -159,7 +159,7 @@ select * from {{
 
 <detailsToggle alt_header="List saved queries">
 
-You can use this example query to list all available saved queries in your dbt project.
+You can use this example query to list all available Saved Queries in your dbt project.
 
 **Command**
 
@@ -536,8 +536,8 @@ semantic_layer.query(metrics=['food_order_amount', 'order_gross_profit'],
   select * from {{ semantic_layer.query(saved_query="new_customer_orders", limit=5, compile=True}}
   ```
 
-:::info A note on querying saved queries
-When querying [saved queries](/docs/build/saved-queries),you can use parameters such as `where`, `limit`, `order`, `compile`, and so on. However, keep in mind that you can't access `metric` or `group_by` parameters in this context. This is because they are predetermined and fixed parameters for saved queries, and you can't change them at query time. If you would like to query more metrics or dimensions, you can build the query using the standard format.
+:::info A note on querying Saved Queries
+When querying [Saved Queries](/docs/build/saved-queries),you can use parameters such as `where`, `limit`, `order`, `compile`, and so on. However, keep in mind that you can't access `metric` or `group_by` parameters in this context. This is because they are predetermined and fixed parameters for Saved Queries, and you can't change them at query time. If you would like to query more metrics or dimensions, you can build the query using the standard format.
 :::
 
 ### Query a saved query
diff --git a/website/docs/docs/dbt-versions/release-notes/72-Feb-2024/exports-rn.md b/website/docs/docs/dbt-versions/release-notes/72-Feb-2024/exports-rn.md
new file mode 100644
index 00000000000..084f458d7d8
--- /dev/null
+++ b/website/docs/docs/dbt-versions/release-notes/72-Feb-2024/exports-rn.md
@@ -0,0 +1,16 @@
+---
+title: "New: Materialize saved queries with Exports"
+description: "February 2024: Use Exports to schedule saved queries with with dbt Cloud and integration with additional tools."
+sidebar_label: "New: Materialize saved queries with Exports"
+sidebar_position: 09
+tags: [Feb-2024]
+date: 2024-02-dd
+---
+
+You can now use [Exports](/docs/use-dbt-semantic-layer/exports) to materialize saved queries in your data platform, on a schedule. It uses the dbt Cloud job scheduler to execute saved queries for reliable and fast data reporting.
+
+Exports enable custom integration with additional tools that don't natively connect with the [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), such as PowerBI.
+
+Exports are available on dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) plans and dbt versions 1.7 or higher.
+
+<Lightbox src="/img/docs/dbt-cloud/semantic-layer/deploy_exports.jpg" width="90%" title="Adding --include-saved-query to the dbt build command in your job execution settings." />
diff --git a/website/docs/docs/dbt-versions/release-notes/73-Jan-2024/jan-sl-updates.md b/website/docs/docs/dbt-versions/release-notes/73-Jan-2024/jan-sl-updates.md
index 3ac3081afd5..e1d1e8f4c24 100644
--- a/website/docs/docs/dbt-versions/release-notes/73-Jan-2024/jan-sl-updates.md
+++ b/website/docs/docs/dbt-versions/release-notes/73-Jan-2024/jan-sl-updates.md
@@ -14,7 +14,7 @@ The following list explains the new features, updates, and fixes for January 202
 
 - **Conversion metrics** &mdash; New metric type that allows you to measure conversion events. For example, users who viewed a web page and then filled out a form. For more details, refer to [Conversion metrics](/docs/build/conversion).
 - **Simplified dimension resolution** &mdash; Instead of specifying the fully qualified dimension name (for example, `order__user__country`) in the group by or filter expression, you now only need to provide the primary entity and dimensions name, like `user__county`.
-- **Saved queries** &mdash; You can now query the [saved queries](/docs/build/saved-queries) you've defined in the dbt Semantic Layer using [Tableau](/docs/use-dbt-semantic-layer/tableau), [GraphQL API](/docs/dbt-cloud-apis/sl-graphql), [JDBC API](docs/dbt-cloud-apis/sl-jdbc), and the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation).
+- **Saved Queries** &mdash; You can now query the [Saved Queries](/docs/build/saved-queries) you've defined in the dbt Semantic Layer using [Tableau](/docs/use-dbt-semantic-layer/tableau), [GraphQL API](/docs/dbt-cloud-apis/sl-graphql), [JDBC API](docs/dbt-cloud-apis/sl-jdbc), and the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation).
 
 ## Updates
 
diff --git a/website/docs/docs/deploy/deployment-overview.md b/website/docs/docs/deploy/deployment-overview.md
index aa7c8b3bdbe..3547e8839ba 100644
--- a/website/docs/docs/deploy/deployment-overview.md
+++ b/website/docs/docs/deploy/deployment-overview.md
@@ -16,7 +16,7 @@ dbt Cloud offers the easiest and most reliable way to run your dbt project in pr
 - Identify the root cause of failures in deployment environments
 - Maintain high-quality code and data in production
 - Gain visibility into the health of deployment jobs, models, and tests
-- Uses [exports](/docs/use-dbt-semantic-layer/exports) to materialize [saved queries](/docs/build/saved-queries) in your data platform for reliable and fast metric reporting
+- Uses [Exports](/docs/use-dbt-semantic-layer/exports) to materialize [Saved Queries](/docs/build/saved-queries) in your data platform for reliable and fast metric reporting
 
 Before continuing, make sure you understand dbt's approach to [deployment environments](/docs/deploy/deploy-environments). 
 
diff --git a/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md b/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md
index eb05fc75649..8427a15cc11 100644
--- a/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md
+++ b/website/docs/docs/use-dbt-semantic-layer/avail-sl-integrations.md
@@ -27,11 +27,11 @@ import AvailIntegrations from '/snippets/_sl-partner-links.md';
 
 ### Custom integration
 
-- You can create custom integrations using different languages and tools. We support connecting with JDBC, ADBC, and GraphQL APIs. For more info, check out [our examples on GitHub](https://github.com/dbt-labs/example-semantic-layer-clients/).
-- You can also connect to tools that allow you to write SQL. These tools must meet one of the two criteria:
-  
-    - Supports a generic JDBC driver option (such as DataGrip) or
-    - Uses Arrow Flight SQL JDBC driver version 12.0.0 or higher.
+- [Exports](/docs/use-dbt-semantic-layer/exports) enable custom integration with additional tools that don't natively connect with the dbt Semantic Layer, such as PowerBI.
+- Develop custom integrations using different languages and tools, supported through JDBC, ADBC, and GraphQL APIs. For more info, check out [our examples on GitHub](https://github.com/dbt-labs/example-semantic-layer-clients/).
+- Connect to any tool that supports SQL queries. These tools must meet one of the two criteria:
+    - Offers a generic JDBC driver option (such as DataGrip) or
+    - Is compatible Arrow Flight SQL JDBC driver version 12.0.0 or higher.
 
 ## Related docs
 
diff --git a/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md b/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md
index 39d79f68d10..4c1f929d45b 100644
--- a/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md
+++ b/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md
@@ -49,7 +49,7 @@ plan="dbt Cloud Team or Enterprise"
 
 <Card
     title="Materialize queries with Exports"
-    body="Use Exports to materialize saved queries within the data platform on a schedule."
+    body="Use Exports to materialize commonly used queries directly within your data platform, on a schedule."
     link="/docs/use-dbt-semantic-layer/exports"
     icon="dbt-bit"/>
 
diff --git a/website/docs/docs/use-dbt-semantic-layer/exports.md b/website/docs/docs/use-dbt-semantic-layer/exports.md
index 01686c36237..6dd05eb4829 100644
--- a/website/docs/docs/use-dbt-semantic-layer/exports.md
+++ b/website/docs/docs/use-dbt-semantic-layer/exports.md
@@ -1,5 +1,5 @@
 ---
-title: "Exports"
+title: "Materialize queries with Exports"
 description: "Use Exports to materialize tables to the data platform on a schedule."
 sidebar_label: "Materialize with Exports"
 ---
@@ -11,7 +11,7 @@ While Saved Queries are a way to save and reuse commonly used queries in MetricF
 - 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 allow you to query metric definition through any SQL interface or connect to downstream tools without needing a first class Semantic Layer integration.
+Essentially, Exports are like any other table in your data platform. They allow you to query metric definition 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.
 
 ## Prerequisites
 
@@ -38,6 +38,8 @@ Exports are an additional configuration added to a Saved Query. They define how
 
 You can define Exports in a YAML format as a key within the `saved_queries` configuration. Here's an example of a Saved Query with an Export:
 
+<File name='saved_queries.yml'>
+
 ```yaml
 saved_queries:
   - name: your_query
@@ -57,6 +59,7 @@ saved_queries:
           schema: your_schema # Optional - defaults to deployment schema
           alias: some_table_name # Optional - defaults to Export name
 ```
+</File>
 
 You can use the following parameters to define an Export:
 
@@ -65,8 +68,8 @@ You can use the following parameters to define an Export:
 | `name` | String    | Required     | Name of the Export object.    |
 | `saved-query` | String    | Required     | A name of a Saved Query that could be used.    |
 | `select` | List or String   | Optional    | Names of Exports to be selected from the Saved Query. |
-| `exclude` | String  | Optional    | Not the names of Exports to be selected from the Saved Query. |
-| `export_as` | String  | Optional    | Type of Export to create from the Export_as types available in the config. |
+| `exclude` | String  | Optional    | The names of Exports to be excluded from the from the Saved Query. |
+| `export_as` | String  | Optional    | Type of Export to create from the `export_as` types available in the config. Options available are `table` or `view`. |
 | `schema` | String  | Optional    | Schema to use for creating the table or view. |
 | `alias` | String  | Optional    | Table alias to use to write the table or view. |
 
@@ -74,12 +77,12 @@ You can use the following parameters to define an Export:
 
 Once you've defined Export in your dbt project, the next step is to run them. There are two ways to run an Export:
   
-1. Run an Export in your development environment using the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation).
-2. Run an Export in your production environment using the [dbt Cloud Job scheduler](/docs/deploy/job-scheduler).
+1. [Run Exports in development](#exports-in-development) using the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation).
+2. [Run Exports in production](#exports-in-production) using the [dbt Cloud Job scheduler](/docs/deploy/job-scheduler).
 
 ### Exports in Development
 
-You can run an Export in your development environment using your development credentials if you want to test the output of the Export using the following command in the dbt Cloud CLI:
+You can run an Export in your development environment using your development credentials if you want to test the output of the Export before production. You can use the following command in the dbt Cloud CLI:
 
 ```bash
 dbt sl export
@@ -95,7 +98,7 @@ dbt sl export --saved-query sq_name
 
 ### Use the `select` flag
 
-By default, all Exports are run for a Saved Query. You can use the `select` flag in [development](#exports-in-development) or [production](#exports-in-production) to select a specific Export or you can specify a new Export using the `export-as` flag. In production, the dbt Cloud Job scheduler runs the equivalent of `dbt sl export --saved-query sq_name`.
+By default, all Exports are run for a Saved Query. You can use the `select` flag in [development](#exports-in-development) or [production](#exports-in-production) to select or exclude a specific Export. 
 
 For example, the following command will run the `export_1` and `export_2` and doesn't work with the `--alias` or `--export_as` flags:
 
@@ -104,24 +107,18 @@ dbt sl export --select export_1,export2
 ```
 
 :::info Overrides and configurations
-The `--select` flag is mainly used to choose specific Exports to run. However, it can't be used with `alias` or `schema` to override the Export configurations.
+The `--select` flag is mainly used to include or exclude specific Exports. However, it can't be used with `alias` or `schema` to override the Export configurations.
 
 If you need to change these settings, use the `--export-as` flag, along with `--schema` and `--alias`. For example, you can use the following command to create a new Export named `new_export` as a table:
 
 ```bash
-dbt sl export --saved_query sq1 --export-as table --alias new_export
+dbt sl export --saved_query sq_number1 --export-as table --alias new_export
 ```
 :::
 
 ### Exports in Production
 
-You can run an Export against your production data by adding the `--include-saved-query flag` in `dbt build` in your deployment **Execution Settings**. For example, `dbt build --include-saved-query`.
-
-You can use the selector syntax `--select` or `-s` to specify a particular dbt model to run in your build command in order to only run the Exports downstream of that model. As an example, the following command will run any Saved Queries that are downstream of the `orders` semantic model:
-
-```bash
-dbt build --include-saved-query --select orders+
-```
+You can run an Export against your production data by adding the `--include-saved-query` flag to the `dbt build` **Commands** box, in your deployment **Execution Settings**. Running `dbt build --include-saved-query` runs the equivalent of `dbt sl export --saved-query sq_name` in the dbt Cloud Job scheduler.
 
 When you run a build job, any Saved Queries downstream of the dbt models in that job will run as well. To make sure your Export data is up-to-date, run the Export as a downstream step (after the model). The steps to create an Export are:
 
@@ -134,21 +131,34 @@ When you run a build job, any Saved Queries downstream of the dbt models in that
 
 <Lightbox src="/img/docs/dbt-cloud/semantic-layer/deploy_exports.jpg" width="90%" title="Adding --include-saved-query to the dbt build command in your job execution settings." />
 
+You can use the selector syntax `--select` or `-s` to specify a particular dbt model to run in your build command in order to only run the Exports downstream of that model. As an example, the following command will run any Saved Queries that are downstream of the `orders` semantic model:
+
+```bash
+dbt build --include-saved-query --select orders+
+```
+
 
 ## FAQs
 
 <detailsToggle alt_header="Can I have multiple Exports in a single saved_query?">
-Yes, this is possible, but the only difference would be the name, schema, and materialization strategy of the Export.
+Yes, this is possible. However, the only difference would be the name, schema, and materialization strategy of the Export.
 </detailsToggle>
 
 <detailsToggle alt_header="How do I run all Exports for a Saved Query?">
-In production runs you build a model and any Exports downstream of that model. There is currently no way to call the Export directly from the Job scheduler. In development, you can run all Exports by running `dbt sl Export --saved-query sq_name`.
+In production runs, you build a model and any Exports downstream of that model. There is currently no way to call the Export directly from the Job scheduler. In development, you can run all Exports by running `dbt sl Export --saved-query sq_name`.
 </detailsToggle>
 
 <detailsToggle alt_header="Will I run duplicate Exports if multiple models are downstream of my Saved Query?">
-We will only run each Export once even if we build multiple models that are downstream of the Saved Query. For example, say I have a Saved Query called `order_metrics`, which has metrics from both the `orders` and `order_items` semantic models. I run a job that includes both models i.e `dbt build --include-saved-query`. This runs both the `order's` and `order_items` models, but will only run the order_metrics Export once.
+We will only run each Export once even if we build multiple models that are downstream of the Saved Query. For example, you may have a Saved Query called `order_metrics`, which has metrics from both the `orders` and `order_items` semantic models. You can run a job that includes both models: `dbt build --include-saved-query`. This runs both the `orders` and `order_items` models, however it will only run the `order_metrics` Export once.
 </detailsToggle>
 
-<detailsToggle alt_header="Can I reference and Export as a dbt model using ref()">
-No. Additional transformation on top of an Export means we wouldn't be able to verify the logic hasn't been changed from the metric definition in the Semantic Layer. For this reason, we think of Exports as a leaf node in your DAG
+<detailsToggle alt_header="Can I reference an Export as a dbt model using ref()">
+No, you won't be able to reference an Export using `ref`. Exports are treated as leaf nodes in your DAG. Modifying an Export cold lead to inconsistencies with the the original metrics from the Semantic Layer.
+</detailsToggle>
+
+<detailsToggle alt_header="How do Exports help me use the dbt Semantic Layer in tools that don't support it, such as PowerBI?">
+
+Exports provide an integration path for tools that don't natively connect with the dbt Semantic Layer by exposing tables of metrics and dimensions in the data platform.
+
+You can use Exports to create a custom integration with tools such as PowerBI, and more.
 </detailsToggle>
diff --git a/website/docs/docs/use-dbt-semantic-layer/tableau.md b/website/docs/docs/use-dbt-semantic-layer/tableau.md
index e055d4dc233..e9c02cd2776 100644
--- a/website/docs/docs/use-dbt-semantic-layer/tableau.md
+++ b/website/docs/docs/use-dbt-semantic-layer/tableau.md
@@ -45,7 +45,7 @@ This integration provides a live connection to the dbt Semantic Layer through Ta
 
 1. **Authentication** &mdash; Once you authenticate, the system will direct you to the data source page. 
 2. **Access all Semantic Layer Objects** &mdash; You can choose between all the metrics, dimensions, and entities configured in your dbt Semantic Layer under the data source called "ALL". (Note: "METRICS_AND_DIMENSIONS" was the original name of this data source, and it contains the same information as "ALL". In the future, we will deprecate "METRICS_AND_DIMENSIONS" in favor of "ALL") 
-3. **Access Saved Queries** &mdash; You can optionally access individual [saved queries](/docs/build/saved-queries) that you've defined. These will also show up as unique data sources when you log in.
+3. **Access Saved Queries** &mdash; You can optionally access individual [Saved Queries](/docs/build/saved-queries) that you've defined. These will also show up as unique data sources when you log in.
 4. **Access worksheet** &mdash; From your data source selection, go directly to a worksheet in the bottom left-hand corner.
 5. **Query metrics and dimensions** &mdash; Then, you'll find all the metrics, dimensions, and entities that are available to query on the left side of your window based on your selection.
 
@@ -62,7 +62,7 @@ Visit the [Tableau documentation](https://help.tableau.com/current/pro/desktop/e
 - The dbt Semantic Layer controls the aggregation type in code and it is intentionally fixed. Keep in mind that the underlying aggregation in the dbt Semantic Layer might not be "SUM" ("SUM" is Tableau's default).
 
 **Data sources and display**<br />
--  In the "ALL" data source, Tableau surfaces all metrics and dimensions from the dbt Semantic Layer on the left-hand side. Note, that not all metrics and dimensions can be combined. You will receive an error message if a particular dimension cannot be sliced with a metric (or vice versa). You can use saved queries for smaller pieces of data that you want to combine.
+-  In the "ALL" data source, Tableau surfaces all metrics and dimensions from the dbt Semantic Layer on the left-hand side. Note, that not all metrics and dimensions can be combined. You will receive an error message if a particular dimension cannot be sliced with a metric (or vice versa). You can use Saved Queries for smaller pieces of data that you want to combine.
 - To display available metrics and dimensions, dbt Semantic Layer returns metadata for a fake table with the dimensions and metrics as 'columns' on this table. Because of this, you can't actually query this table for previews or extracts.
 
 **Calculations and querying**<br />
diff --git a/website/docs/guides/sl-partner-integration-guide.md b/website/docs/guides/sl-partner-integration-guide.md
index 21ea822389f..853f35827a8 100644
--- a/website/docs/guides/sl-partner-integration-guide.md
+++ b/website/docs/guides/sl-partner-integration-guide.md
@@ -52,7 +52,7 @@ Best practices for exposing metrics are summarized into five themes:
 
 - [Governance](#governance-and-traceability) &mdash; Recommendations on how to establish guardrails for governed data work.
 - [Discoverability](#discoverability) &mdash; Recommendations on how to make user-friendly data interactions.
-- [Organization](#organization) &mdash; Organize metrics and dimensions for all audiences, use [saved queries](/docs/build/saved-queries).
+- [Organization](#organization) &mdash; Organize metrics and dimensions for all audiences, use [Saved Queries](/docs/build/saved-queries).
 - [Query flexibility](#query-flexibility) &mdash; Allow users to query either one metric alone without dimensions or multiple metrics with dimensions.
 - [Context and interpretation](#context-and-interpretation) &mdash; Contextualize metrics for better analysis; expose definitions, metadata, lineage, and freshness.
 
@@ -91,7 +91,7 @@ We recommend organizing metrics and dimensions in ways that a non-technical user
 
 - **Organizing metrics** &mdash; The goal is to organize metrics into a hierarchy in our configurations, instead of presenting them in a long list.<br /><br /> This hierarchy helps you organize metrics based on specific criteria, such as business unit or team. By providing this structured organization, users can find and navigate metrics more efficiently, enhancing their overall data analysis experience.
 
-- **Using Saved queries** &mdash; The dbt Semantic Layer has a concept of [saved queries](/docs/build/saved-queries) which allows users to pre-build slices of metrics, dimensions, filters to be easily accessed. You should surface these as first class objects in your integration. Refer to the [JDBC](/docs/dbt-cloud-apis/sl-jdbc) and [GraphQL](/docs/dbt-cloud-apis/sl-graphql) APIs for syntax.
+- **Using Saved Queries** &mdash; The dbt Semantic Layer has a concept of [Saved Queries](/docs/build/saved-queries) which allows users to pre-build slices of metrics, dimensions, filters to be easily accessed. You should surface these as first class objects in your integration. Refer to the [JDBC](/docs/dbt-cloud-apis/sl-jdbc) and [GraphQL](/docs/dbt-cloud-apis/sl-graphql) APIs for syntax.
 
 ### Query flexibility
 
@@ -148,7 +148,7 @@ These are recommendations on how to evolve a Semantic Layer integration and not
 * Listing available dimensions based on one or many metrics
 * Querying defined metric values on their own or grouping by available dimensions
 * Display metadata from [Discovery API](/docs/dbt-cloud-apis/discovery-api) and other context
-* Expose [Saved queries](/docs/build/saved-queries), which are pre-built metrics, dimensions, and filters that Semantic Layer developers create for easier analysis. You can expose them in your application. Refer to the [JDBC](/docs/dbt-cloud-apis/sl-jdbc) and [GraphQL](/docs/dbt-cloud-apis/sl-graphql) APIs for syntax.
+* Expose [Saved Queries](/docs/build/saved-queries), which are pre-built metrics, dimensions, and filters that Semantic Layer developers create for easier analysis. You can expose them in your application. Refer to the [JDBC](/docs/dbt-cloud-apis/sl-jdbc) and [GraphQL](/docs/dbt-cloud-apis/sl-graphql) APIs for syntax.
 
 **Stage 3 - More querying flexibility and better user experience (UX)**
 * More advanced filtering
diff --git a/website/snippets/_sl-connect-and-query-api.md b/website/snippets/_sl-connect-and-query-api.md
index f7f1d2add24..c155af4d11e 100644
--- a/website/snippets/_sl-connect-and-query-api.md
+++ b/website/snippets/_sl-connect-and-query-api.md
@@ -1,8 +1,8 @@
-You can query your metrics in a JDBC-enabled tool or use existing first-class integrations with the dbt Semantic Layer. 
+You can query your metrics in a JDBC-enabled tool or use existing first-class integrations with the dbt Semantic Layer.  
 
 - You must have a dbt Cloud Team or Enterprise account. Suitable for both Multi-tenant and Single-tenant deployment.
   - Single-tenant accounts should contact their account representative for necessary setup and enablement.
 - To learn how to use the JDBC or GraphQL API and what tools you can query it with, refer to [dbt Semantic Layer APIs](/docs/dbt-cloud-apis/sl-api-overview).
     * To authenticate, you need to [generate a service token](/docs/dbt-cloud-apis/service-tokens) with Semantic Layer Only and Metadata Only permissions.
     * Refer to the [SQL query syntax](/docs/dbt-cloud-apis/sl-jdbc#querying-the-api-for-metric-metadata) to query metrics using the API.  
-- To learn more about the sophisticated integrations that connect to the dbt Semantic Layer, refer to [Available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) for more info.
+- To learn more about the sophisticated integrations that connect to the dbt Semantic Layer, refer to [Available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) for more info. You can also use [Exports](/docs/use-dbt-semantic-layer/exports) to expose tables of metrics and dimensions in your data platform and create a custom integration with tools such as PowerBI, and more.