sl beta docs

website/dbt-versions.js

@@ -183,6 +183,22 @@ exports.versionedPages = [
     "page": "docs/build/ratio",
     "firstVersion": "1.6",
   },
+  {
+    "category": "docs/use-dbt-semantic-layer/sl-api-overview",
+    "firstVersion": "1.6",
+  },
+	{
+    "category": "docs/use-dbt-semantic-layer/graphql",
+    "firstVersion": "1.6",
+  },
+	{
+    "category": "docs/use-dbt-semantic-layer/jdbc",
+    "firstVersion": "1.6",
+  },
+  {
+    "category": "docs/use-dbt-semantic-layer/sl-manifest",
+    "firstVersion": "1.6",
+  },
 ]
 
 exports.versionedCategories = [
@@ -193,5 +209,9 @@ exports.versionedCategories = [
   {
     "category": "Build your metrics",
     "firstVersion": "1.6",
+  },
+  {
+    "category": "Semantic Layer APIs",
+    "firstVersion": "1.6",
   }
 ]

website/docs/docs/build/about-metricflow.md

@@ -10,7 +10,7 @@ This guide introduces MetricFlow's fundamental ideas for new users. MetricFlow,
 
 :::info
 
-MetricFlow is a new way to define metrics in dbt and one of the key components of the [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-semantic-layer). It handles SQL query construction and defines the specification for dbt semantic models and metrics. 
+MetricFlow is a new way to define metrics in dbt and one of the key components of the [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl). It handles SQL query construction and defines the specification for dbt semantic models and metrics. 
 
 To fully experience the dbt Semantic Layer, including the ability to query dbt metrics via external integrations, you'll need a [dbt Cloud Team or Enterprise account](https://www.getdbt.com/pricing/).
 

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

@@ -7,49 +7,60 @@ tags: [Metrics, Semantic Layer, Governance]
 hide_table_of_contents: true
 ---
 
-Use MetricFlow in dbt to centrally define your metrics. MetricFlow is a key component of the [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-semantic-layer) and is responsible for SQL query construction and defining specifications for dbt semantic models and metrics.
+Use MetricFlow in dbt to centrally define your metrics. MetricFlow is a key component of the [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) and is responsible for SQL query construction and defining specifications for dbt semantic models and metrics.
 
 Use familiar constructs like semantic models and metrics to avoid duplicative coding, optimize your development workflow, ensure data governance for company metrics, and guarantee consistency for data consumers.
 
 :::info
-MetricFlow is currently available on dbt Core v1.6 beta for [command line (CLI)](/docs/core/about-the-cli) users, with support for dbt Cloud and integrations coming soon. MetricFlow, a BSL package (code is source available), is a new way to define metrics in dbt and will replace the dbt_metrics package.
+MetricFlow is currently available on dbt v1.6 or higher. MetricFlow, is a new way to define metrics in dbt and  replaces the dbt_metrics package.
 
 To fully experience the dbt Semantic Layer, including the ability to query dbt metrics via external integrations, you'll need a [dbt Cloud Team or Enterprise account](https://www.getdbt.com/pricing/).
 :::
 
 Before you start, keep the following considerations in mind:
-- Use the CLI to define metrics in YAML and query them using the [new metric specifications](https://github.com/dbt-labs/dbt-core/discussions/7456).
-- You must be on dbt Core v1.6 beta or higher to use MetricFlow. [Upgrade your dbt version](/docs/core/pip-install#change-dbt-core-versions) to get started.
-  * Note: Support for dbt Cloud and querying via external integrations coming soon.
-- MetricFlow currently only supports Snowflake and Postgres.
-  * Note: Support for BigQuery, Databricks, and Redshift coming soon.
-- dbt Labs is working with [integration partners](https://www.getdbt.com/product/semantic-layer-integrations) to develop updated integrations for the new Semantic Layer, powered by MetricFlow, in addition to introducing other consumption methods like Python and JDBC. <br /><br />
+- Define metrics in YAML and query them using the [new metric specifications](https://github.com/dbt-labs/dbt-core/discussions/7456).
+- You must be on dbt v1.6 or higher to use MetricFlow. [Upgrade your dbt Cloud version](/docs/dbt-versions/upgrade-core-in-cloud) to get started.
+- MetricFlow currently supports Snowflake, Postgres, BigQuery, Databricks, and Redshift.
+- Unlock insights and query your metrics using the [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) and its diverse range of [available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations).
 
-<div className="grid--4-col">
+<div className="grid--3-col">
 
 <Card
     title="About MetricFlow"
     body="Understand MetricFlow's core concepts, key principles, and how to use this powerful tool."
     link="/docs/build/about-metricflow"
-    icon="rocket"/>
-
-<Card
-    title="Get started with MetricFlow"
-    body="Learn how to create a semantic model, a metric, and test and upload your metric using MetricFlow."
-    link="/docs/build/sl-getting-started"
-    icon="rocket"/>
+    icon="dbt-bit"/>
 
   <Card
     title="Semantic model"
-    body="Use Semantic models as the basis for defining data. They act as nodes in the semantic graph, with entities connecting them."
+    body="Use semantic models as the basis for defining data. They act as nodes in the semantic graph, with entities connecting them."
     link="/docs/build/semantic-models"
-    icon="rocket"/>
+    icon="dbt-bit"/>
 
   <Card
     title="Metrics"
     body="Define metrics through the powerful combination of measures, constraints, or functions, effortlessly organized in either YAML files or separate files."
     link="/docs/build/metrics-overview"
-    icon="rocket"/>   
+    icon="dbt-bit"/>
+
+  <Card
+    title="About the dbt Semantic Layer"
+    body="Introducing the dbt Semantic Layer, the universal process that allows data teams to centrally define and query metrics"
+    link="/docs/use-dbt-semantic-layer/dbt-sl"
+    icon="dbt-bit"/>
+
+ <Card
+    title="Get started with the dbt Semantic Layer"
+    body="Use this guide to build and define metrics, set up the dbt Semantic Layer, and query them using the Semantic Layer APIs"
+    link="/docs/use-dbt-semantic-layer/quickstart-sl"
+    icon="dbt-bit"/>
+
+  <Card
+    title="Available integrations"
+    body="Discover the diverse range of partners that seamlessly integrate with the powerful dbt Semantic Layer, allowing you to query and unlock valuable insights from your data ecosystem."
+    link="/docs/use-dbt-semantic-layer/avail-sl-integrations"
+    icon="dbt-bit"/>
+
 
 </div> <br />
 

website/docs/docs/build/metrics.md

@@ -4,33 +4,41 @@ id: "metrics"
 description: "When you define metrics in dbt projects, you encode crucial business logic in tested, version-controlled code. The dbt metrics layer helps you standardize metrics within your organization."
 keywords:
   - dbt metrics layer
+tags: [Metrics]
 ---
 
-<VersionBlock firstVersion="1.6">
+:::caution Upgrade to access MetricFlow and the new dbt Semantic Layer
 
-:::info dbt Metrics isn't supported
+The dbt_metrics package has been deprecated and replaced with [MetricFlow](/docs/build/about-metricflow?version=1.6). If you're using the dbt_metrics package or the legacy Semantic Layer (available on v1.5 or lower), we **highly** recommend [upgrading your dbt version](/docs/dbt-versions/upgrade-core-in-cloud) to dbt v1.6 or higher to access MetricFlow and the new [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl?version=1.6).
 
-dbt Metrics is no longer supported in v1.6 and higher. To build your semantic layer, define and query metrics, and provide data governance - refer to [Build your Semantic Layer](/docs/build/build-metrics-intro) for updated guidance.
+To migrate to the new Semantic Layer, refer to the dedicated [migration guide](/guides/migration/sl-migration) for more info.
 
 :::
-</VersionBlock>
+
+<VersionBlock firstVersion="1.6">
 
-<VersionBlock lastVersion="1.5">
+The dbt Semantic Layer has undergone a [significant revamp](https://www.getdbt.com/blog/dbt-semantic-layer-whats-next/), improving governance, introducing new APIs, and making it more efficient to define/query metrics. This revamp means the dbt_metrics package and the legacy Semantic Layer, available in dbt v1.5 or lower, are no longer supported and won't receive any code fixes.
 
-:::info dbt Metrics not recommended
+**What’s changed?** <br /> <br />
+The dbt_metrics package has been [deprecated](https://docs.getdbt.com/blog/deprecating-dbt-metrics) and replaced with [MetricFlow](/docs/build/about-metricflow?version=1.6), a new framework for defining metrics in dbt. This means dbt_metrics is no longer supported after dbt v1.5 and won't receive any code fixes. We will also remove the dbt_metrics spec and docs when it's fully deprecated. 
 
-dbt Metrics won't be supported in v1.6 and higher, and is being replaced with MetricFlow. [Defining metrics](/docs/build/build-semantic-layer-intro) with MetricFlow will help shape the future of the dbt Semantic Layer &mdash; let us know [your thoughts and join the convo](https://github.com/dbt-labs/dbt-core/discussions/7456) to help build it!
+**Who does this affect?** <br /> <br />
+Anyone who uses the dbt_metrics package or is integrated with the legacy Semantic Layer. The new Semantic Layer is available to [Team or Enterprise](https://www.getdbt.com/pricing/) multi-tenant dbt Cloud plans [hosted in North America](/docs/cloud/about-cloud/regions-ip-addresses). You must be on dbt v1.6 or higher to access it. All users can define metrics using MetricFlow. Users on dbt Cloud Developer plans or dbt Core can only use it to define and test metrics locally, but can't dynamically query them with integrated tools.
 
-:::
+**What should you do?** <br /> <br />
+If you've defined metrics using dbt_metrics or integrated with the legacy Semantic Layer, we **highly** recommend you [upgrade your dbt version](/docs/dbt-versions/upgrade-core-in-cloud) to dbt v1.6 or higher to use MetricFlow or the new dbt Semantic Layer. To migrate to the new Semantic Layer, refer to the dedicated [migration guide](/guides/migration/sl-migration) for more info.
 
 
+</VersionBlock>
+
+<VersionBlock lastVersion="1.5">
+
 <Changelog>
 
 * **v1.3.0**: Metrics have been moved out of the experimental phase
 * **v1.0.0**: Metrics are new and experimental
 
 </Changelog>
-
 
 A metric is an aggregation over a <Term id="table" /> that supports zero or more dimensions. Some examples of metrics include:
 - active users
@@ -59,7 +67,7 @@ You can define metrics in `.yml` files nested under a `metrics:` key. Metric nam
 - begin with a letter
 - contain no more than 250 characters
 
-For a short human-friendly name with title casing, spaces, and special characters, use the `label` property. More examples and guidance for how to [define and structure metrics can be found here.](https://docs.getdbt.com/blog/how-to-design-and-structure-metrics).
+For a short human-friendly name with title casing, spaces, and special characters, use the `label` property. 
 
 ### Example definition
 
@@ -218,9 +226,12 @@ Metrics can have many declared **properties**, which define aspects of your metr
 ### Available calculation methods
 
 <VersionBlock firstVersion="1.3">
+
 The method of calculation (aggregation or derived) that is applied to the expression.
 </VersionBlock> 
+
 <VersionBlock lastVersion="1.2">
+
 The type of calculation (aggregation or expression) that is applied to the sql property.
 </VersionBlock> 
 
@@ -428,6 +439,11 @@ The following is the list of currently accepted metric configs:
 </VersionBlock>
 
 ## Querying Your Metric
+
+:::caution dbt_metrics is no longer supported
+The dbt_metrics package has been deprecated and replaced with [MetricFlow](/docs/build/about-metricflow?version=1.6), a new way framework for defining metrics in dbt. This means dbt_metrics is no longer supported after dbt v1.5 and won't receive any code fixes.
+:::
+
 You can dynamically query metrics directly in dbt and verify them before running a job in the deployment environment.  To query your defined metric, you must have the [dbt_metrics package](https://github.com/dbt-labs/dbt_metrics) installed. Information on how to [install packages can be found here](https://docs.getdbt.com/docs/build/packages#how-do-i-add-a-package-to-my-project).
 
 Use the following [metrics package](https://hub.getdbt.com/dbt-labs/metrics/latest/) installation code in your packages.yml file and run `dbt deps` to install the metrics package:
@@ -541,6 +557,7 @@ The period to date secondary calculation performs an aggregation on a defined pe
 #### Rolling:
 
 <VersionBlock firstVersion="1.3" >
+
 The rolling secondary calculation performs an aggregation on a number of rows in metric dataset. For example, if the user selects the `week` grain and sets a rolling secondary calculation to `4` then the value returned will be a rolling 4 week calculation of whatever aggregation type was selected. If the `interval` input is not provided then the rolling caclulation will be unbounded on all preceding rows.
 
 | Input                      | Example | Description | Required |
@@ -552,6 +569,7 @@ The rolling secondary calculation performs an aggregation on a number of rows in
 </VersionBlock>
 
 <VersionBlock lastVersion="1.2" >
+
 The rolling secondary calculation performs an aggregation on a number of rows in the metric dataset. For example, if the user selects the `week` grain and sets a rolling secondary calculation to `4`, then the value returned will be a rolling 4-week calculation of whatever aggregation type was selected.
 
 | Input                      | Example | Description | Required |
@@ -715,4 +733,6 @@ The above example will return a dataset that contains the metric provided in the
 </VersionBlock>
 
 <Snippet path="discourse-help-feed-header" />
+
 <DiscourseHelpFeed tags="metrics"/>
+

website/docs/docs/build/sl-getting-started.md

@@ -126,6 +126,7 @@ ANY COMMON TROUBLESHOOTING QUESTIONS?-->
 
 ## Related docs
 
+- [Get started with the dbt Semantic Layer](/docs/use-dbt-semantic-layer/quickstart-sl)
 - [The dbt Semantic Layer: what’s next](https://www.getdbt.com/blog/dbt-semantic-layer-whats-next/) blog post
 - [About MetricFlow](/docs/build/about-metricflow)
 - [Semantic models](/docs/build/semantic-models)

website/docs/docs/cloud/about-cloud/dbt-cloud-features.md

@@ -63,7 +63,7 @@ link="/docs/cloud/dbt-cloud-ide/develop-in-the-cloud"
    <Card
     title="dbt Semantic Layer*"
     body="Use the dbt Semantic Layer to define metrics alongside your dbt models and query them from any integrated analytics tool. Get the same answers everywhere, every time."
-    link="/docs/use-dbt-semantic-layer/dbt-semantic-layer"
+    link="/docs/use-dbt-semantic-layer/dbt-sl"
     icon="pencil-paper"/>  
 
    <Card

website/docs/docs/dbt-cloud-apis/apis-overview.md

@@ -8,10 +8,11 @@ id: "overview"
 
 Accounts on the _Team_ and _Enterprise_ plans can query the dbt Cloud APIs.
 
-dbt Cloud provides two APIs:
+dbt Cloud provides the following APIs:
 
 - The [dbt Cloud Administrative API](/docs/dbt-cloud-apis/admin-cloud-api) can be used to administrate a dbt Cloud account.
 - The [dbt Cloud Discovery API](/docs/dbt-cloud-apis/discovery-api) can be used to fetch metadata related to the state and health of your dbt project.
+- The [dbt Semantic Layer APIs](/docs/dbt-cloud-apis/sl-api-overview) provides multiple API options which allow you to query your metrics defined in the dbt Semantic Layer.
 
 If you want to learn more about webhooks, refer to [Webhooks for your jobs](/docs/deploy/webhooks).
 

website/docs/docs/dbt-cloud-apis/service-tokens.md

@@ -9,8 +9,6 @@ If you have service tokens created on or before July 18, 2023, please read [this
 
 :::
 
-## About service tokens
-
 Service account tokens enable you to securely authenticate with the dbt Cloud API by assigning each token a narrow set of permissions that more precisely manages access to the API. While similar to [User API tokens](user-tokens), service account tokens belong to an account rather than a user.
 
 You can use service account tokens for system-level integrations that do not run on behalf of any one user. Assign any permission sets available in dbt Cloud to your service account token, which can vary slightly depending on your plan:
@@ -43,6 +41,9 @@ Account Admin service tokens have full `read + write` access to an account, so p
 **Metadata Only**<br/>
 Metadata-only service tokens authorize requests to the Discovery API.
 
+**Semantic Layer Only**<br/>
+Semantic Layer-only service tokens authorize requests to the Semantic Layer APIs.
+
 **Job Admin**<br/>
 Job admin service tokens can authorize requests for viewing, editing, and creating environments, triggering runs, and viewing historical runs.  
 
@@ -68,6 +69,9 @@ Billing Admin service tokens have certain account-level permissions.  For more o
 **Metadata Only**<br/>
 Metadata-only service tokens authorize requests to the Discovery API.
 
+**Semantic Layer Only**<br/>
+Semantic Layer-only service tokens authorize requests to the Semantic Layer APIs.
+
 **Job Admin**<br/>
 Job Admin service tokens can authorize requests for viewing, editing, and creating environments, triggering runs, and viewing historical runs. For more on these permissions, see [Job Admin](/docs/cloud/manage-access/enterprise-permissions#job-admin).
 

website/docs/docs/dbt-cloud-apis/sl-api-overview.md

@@ -0,0 +1,55 @@
+---
+title: "Semantic Layer APIs"
+id: sl-api-overview
+description: "Integrate and query using the Semantic Layer API."
+tags: [Semantic Layer, APIs]
+hide_table_of_contents: true
+---
+
+<VersionBlock lastVersion="1.5">
+
+import LegacyInfo from '/snippets/_legacy-sl-callout.md';
+
+<LegacyInfo />
+
+</VersionBlock>
+
+The rapid growth of different tools in the modern data stack has helped data professionals address the diverse needs of different teams. The downside of this growth is the fragmentation of business logic across teams, tools, and workloads.
+
+The [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) allows users to define metrics in code (with [MetricFlow](/docs/build/about-metricflow)) and dynamically generate and query datasets in downstream tools based on their dbt governed assets, such as metrics and models. Integrating with the dbt Semantic Layer will help the organizations that uses your product make more efficient and trustworthy decisions with their data. It also helps avoid duplicative coding, optimizes development workflow, ensures data governance, and guarantee consistency for data consumers.  
+
+You can use the dbt Semantic Layer for a variety of tools and applications of data. Here are some common use cases:
+
+* Business intelligence (BI), reporting, and analytics
+* Data quality and monitoring
+* Governance and privacy
+* Data discovery and cataloging
+* Machine learning and data science
+
+The dbt Semantic Layer APIs are available for accounts on [Team or Enterprise plans](https://www.getdbt.com/pricing/), allowing them to query metrics and build integrations. Users on dbt Cloud Developer plans or dbt Core users can use MetricFlow to only define and test metrics locally. 
+
+<div className="grid--3-col">
+
+<Card
+    title="JDBC API"
+    body="Use a JDBC driver to query metrics in downstream tools."
+    link="/docs/dbt-cloud-apis/sl-jdbc"
+    icon="dbt-bit"/>
+
+<Card
+    title="GraphQL API"
+    body="Use GraphQL to query metrics in downstream tools."
+    link="/docs/dbt-cloud-apis/sl-graphql"
+    icon="dbt-bit"/>
+
+<Card
+    title="Semantic manifest"
+    body="Learn about the semantic manifest.json file and how you can use artifacts to gain insights about your Semantic Layer."
+    link="/docs/dbt-cloud-apis/sl-manifest"
+    icon="dbt-bit"/>
+
+</div>
+
+## Authentication
+
+dbt Cloud authorizes requests to the dbt Semantic Layer APIs. You need to provide an environment ID, host, and [service account tokens](/docs/dbt-cloud-apis/service-tokens).