Merge branch 'current' into mwong-sql

.github/ISSUE_TEMPLATE/a-improve-docs.yml

@@ -5,7 +5,7 @@ body:
   - type: markdown
     attributes:
       value: |
-        * You can ask questions or submit ideas for the dbt docs in [Discussions](https://github.com/dbt-labs/docs.getdbt.com/discussions)
+        * You can ask questions or submit ideas for the dbt docs in [Issues](https://github.com/dbt-labs/docs.getdbt.com/issues/new/choose)
         * Before you file an issue read the [Contributing guide](https://github.com/dbt-labs/docs.getdbt.com#contributing).
         * Check to make sure someone hasn't already opened a similar [issue](https://github.com/dbt-labs/docs.getdbt.com/issues).
 

.github/ISSUE_TEMPLATE/improve-the-site.yml

@@ -5,7 +5,7 @@ body:
   - type: markdown
     attributes:
       value: |
-        * You can ask questions or submit ideas for the dbt docs in [Discussions](https://github.com/dbt-labs/docs.getdbt.com/discussions)
+        * You can ask questions or submit ideas for the dbt docs in [Issues](https://github.com/dbt-labs/docs.getdbt.com/issues/new/choose)
         * Before you file an issue read the [Contributing guide](https://github.com/dbt-labs/docs.getdbt.com#contributing).
         * Check to make sure someone hasn't already opened a similar [issue](https://github.com/dbt-labs/docs.getdbt.com/issues).
 

.github/labeler.yml

@@ -3,6 +3,7 @@ developer blog:
 
 guides:
 - website/docs/guides/**/*
+- website/docs/quickstarts/**/*
 
 content:
 - website/docs/**/*

.github/workflows/labeler.yml

@@ -5,8 +5,8 @@
 
 name: "Pull Request Labeler"
 on:
-- pull_request_target
-
+  pull_request_target:
+    types: [opened]
 jobs:
   triage:
     permissions:

README.md

@@ -17,7 +17,7 @@ Creating an inclusive and equitable environment for our documents is more import
 We welcome contributions from community members to this repo:
 - **Fixes**: When you notice an error, you can use the `Edit this page` button at the bottom of each page to suggest a change.
 - **New documentation**: If you contributed code in [dbt-core](https://github.com/dbt-labs/dbt-core), we encourage you to also write the docs here! Please reach out in the dbt community if you need help finding a place for these docs.
-- **Major rewrites**: You can [file an issue](https://github.com/dbt-labs/docs.getdbt.com/issues/new?assignees=&labels=content%2Cimprovement&template=improve-docs.yml) or [start a discussion](https://github.com/dbt-labs/docs.getdbt.com/discussions) to propose ideas for a content area that requires attention.
+- **Major rewrites**: You can [file an issue](https://github.com/dbt-labs/docs.getdbt.com/issues/new/choose) to propose ideas for a content area that requires attention.
 
 You can use components documented in the [docusaurus library](https://v2.docusaurus.io/docs/markdown-features/).
 

website/dbt-versions.js

@@ -27,6 +27,10 @@ exports.versions = [
 ]
 
 exports.versionedPages = [
+  {
+    "page": "reference/resource-configs/store_failures_as",
+    "firstVersion": "1.7",
+  },
   {
     "page": "docs/build/build-metrics-intro",
     "firstVersion": "1.6",
@@ -170,6 +174,10 @@ exports.versionedPages = [
   {
     "page": "reference/resource-configs/grants",
     "firstVersion": "1.2",
+  },
+  {
+    "page": "docs/build/saved-queries",
+    "firstVersion": "1.7",
   }
 ]
 

website/docs/community/resources/oss-expectations.md

@@ -4,7 +4,7 @@ title: "Expectations for OSS contributors"
 
 Whether it's a dbt package, a plugin, `dbt-core`, or this very documentation site, contributing to the open source code that supports the dbt ecosystem is a great way to level yourself up as a developer, and to give back to the community. The goal of this page is to help you understand what to expect when contributing to dbt open source software (OSS). While we can only speak for our own experience as open source maintainers, many of these guidelines apply when contributing to other open source projects, too.
 
-Have you seen things in other OSS projects that you quite like, and think we could learn from? [Open a discussion on the Developer Hub](https://github.com/dbt-labs/docs.getdbt.com/discussions/new), or start a conversation in the dbt Community Slack (for example: `#community-strategy`, `#dbt-core-development`, `#package-ecosystem`, `#adapter-ecosystem`). We always appreciate hearing from you!
+Have you seen things in other OSS projects that you quite like, and think we could learn from? [Open a discussion on the dbt Community Forum](https://discourse.getdbt.com), or start a conversation in the dbt Community Slack (for example: `#community-strategy`, `#dbt-core-development`, `#package-ecosystem`, `#adapter-ecosystem`). We always appreciate hearing from you!
 
 ## Principles
 
@@ -51,7 +51,7 @@ An issue could be a bug you’ve identified while using the product or reading t
 
 ### Best practices for issues
 
-- Issues are **not** for support / troubleshooting / debugging help. Please [open a discussion on the Developer Hub](https://github.com/dbt-labs/docs.getdbt.com/discussions/new), so other future users can find and read proposed solutions. If you need help formulating your question, you can post in the `#advice-dbt-help` channel in the [dbt Community Slack](https://www.getdbt.com/community/).
+- Issues are **not** for support / troubleshooting / debugging help. Please [open a discussion on the dbt Community Forum](https://discourse.getdbt.com), so other future users can find and read proposed solutions. If you need help formulating your question, you can post in the `#advice-dbt-help` channel in the [dbt Community Slack](https://www.getdbt.com/community/).
 - Always search existing issues first, to see if someone else had the same idea / found the same bug you did.
 - Many repositories offer templates for creating issues, such as when reporting a bug or requesting a new feature. If available, please select the relevant template and fill it out to the best of your ability. This will help other people understand your issue and respond.
 

website/docs/community/resources/viewpoint.md

@@ -7,7 +7,7 @@ id: "viewpoint"
 
 In 2015-2016, a team of folks at RJMetrics had the opportunity to observe, and participate in, a significant evolution of the analytics ecosystem. The seeds of dbt were conceived in this environment, and the viewpoint below was written to reflect what we had learned and how we believed the world should be different. **dbt is our attempt to address the workflow challenges we observed, and as such, this viewpoint is the most foundational statement of the dbt project's goals.**
 
-The remainder of this document is largely unedited from [the original post](https://blog.getdbt.com/building-a-mature-analytics-workflow/).
+The remainder of this document is largely unedited from [the original post](https://getdbt.com/blog/building-a-mature-analytics-workflow).
 
 :::
 

website/docs/docs/about-setup.md

@@ -3,11 +3,13 @@ title: About dbt setup
 id: about-setup
 description: "About setup of dbt Core and Cloud"
 sidebar_label: "About dbt setup"
+pagination_next: "docs/environments-in-dbt"
+pagination_prev: null
 ---
 
 dbt compiles and runs your analytics code against your data platform, enabling you and your team to collaborate on a single source of truth for metrics, insights, and business definitions. There are two options for deploying dbt:
 
-**dbt Cloud** runs dbt Core in a hosted (single or multi-tenant) environment with a browser-based interface. The intuitive UI will aid you in setting up the various components. dbt Cloud comes equipped with turnkey support for scheduling jobs, CI/CD, hosting documentation, monitoring & alerting, and an integrated developer environment (IDE).
+**dbt Cloud** runs dbt Core in a hosted (single or multi-tenant) environment with a browser-based interface. The intuitive user interface aids you in setting up the various components. dbt Cloud comes equipped with turnkey support for scheduling jobs, CI/CD, hosting documentation, monitoring, and alerting. It also offers an integrated development environment (IDE) and allows you to develop and run dbt commands from your local command line (CLI) or code editor.
 
 **dbt Core** is an open-source command line tool that can be installed locally in your environment, and communication with databases is facilitated through adapters.
 
@@ -19,7 +21,7 @@ To begin configuring dbt now, select the option that is right for you.
 
 <Card
     title="dbt Cloud setup"
-    body="Learn how to connect to a data platform, integrate with secure authentication methods, configure a sync with a git repo, and how to use the IDE."
+    body="Learn how to connect to a data platform, integrate with secure authentication methods, configure a sync with a git repo, how to use the IDE, and how to install the dbt Cloud CLI."
     link="/docs/cloud/about-cloud-setup"
     icon="dbt-bit"/>
 

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

@@ -4,38 +4,56 @@ id: about-metricflow
 description: "Learn more about MetricFlow and its key concepts"
 sidebar_label: About MetricFlow
 tags: [Metrics, Semantic Layer]
+pagination_next: "docs/build/join-logic"
+pagination_prev: null
 ---
 
-This guide introduces MetricFlow's fundamental ideas for new users. MetricFlow, which powers the dbt Semantic Layer, helps you define and manage the logic for your company's metrics. It's an opinionated set of abstractions and helps data consumers retrieve metric datasets from a data platform quickly and efficiently.
+This guide introduces MetricFlow's fundamental ideas for people new to this feature. MetricFlow, which powers the dbt Semantic Layer, helps you define and manage the logic for your company's metrics. It's an opinionated set of abstractions and helps data consumers retrieve metric datasets from a data platform quickly and efficiently. 
 
-:::info
+MetricFlow handles SQL query construction and defines the specification for dbt semantic models and metrics. It allows you to define metrics in your dbt project and query them with [MetricFlow commands](/docs/build/metricflow-commands) whether in dbt Cloud or dbt Core.
 
-MetricFlow is a new way to define metrics 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. 
+Before you start, consider the following guidelines:
 
-MetricFlow is currently available on dbt v1.6 or higher for all users. dbt Core users can use the MetricFlow CLI to define metrics in their local dbt Core project. However, to experience the power of the universal [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) and query those metrics in downstream tools, you'll need a dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) account. 
+- Define metrics in YAML and query them using these [new metric specifications](https://github.com/dbt-labs/dbt-core/discussions/7456).
+- You must be on [dbt version](/docs/dbt-versions/upgrade-core-in-cloud) 1.6 or higher to use MetricFlow. 
+- Use MetricFlow with Snowflake, BigQuery, Databricks, Postgres (dbt Core only), or Redshift. 
+- Discover 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).  You must have a dbt Cloud account on the [Team or Enterprise plan](https://www.getdbt.com/pricing/). 
 
-:::
+## MetricFlow
 
-There are a few key principles:
+MetricFlow is a SQL query generation tool designed to streamline metric creation across different data dimensions for diverse business needs. 
+- It operates through YAML files, where a semantic graph links language to data. This graph comprises [semantic models](/docs/build/semantic-models) (data entry points) and [metrics](/docs/build/metrics-overview) (functions for creating quantitative indicators).
+- MetricFlow is a [BSL package](https://github.com/dbt-labs/metricflow) with code source available, and compatible with dbt version 1.6 and higher. Data practitioners and enthusiasts are highly encouraged to contribute.
+- As a part of the dbt Semantic Layer, MetricFlow empowers organizations to define metrics using YAML abstractions.
+- To query metric dimensions, dimension values, and validate configurations, use [MetricFlow commands](/docs/build/metricflow-commands).
 
-- **Flexible, but complete** —  Ability to create any metric on any data model by defining logic in flexible abstractions.
-- **Don't Repeat Yourself (DRY)** — Avoid repetition by allowing metric definitions to be enabled whenever possible.
-- **Simple with progressive complexity** — Make MetricFlow approachable by relying on known concepts and structures in data modeling. 
-- **Performant and efficient** — Allow for performance optimizations in centralized data engineering while still enabling distributed definition and ownership of logic.
 
-## MetricFlow
+**Note** — MetricFlow doesn't support dbt [builtin functions or packages](/reference/dbt-jinja-functions/builtins) at this time, however, support is planned for the future.
+
+MetricFlow abides by these principles:
 
-- MetricFlow is a SQL query generation engine that helps you create metrics by constructing appropriate queries for different granularities and dimensions that are useful for various business applications. 
+- **Flexibility with completeness**: Define metric logic using flexible abstractions on any data model.
+- **DRY (Don't Repeat Yourself)**: Minimize redundancy by enabling metric definitions whenever possible.
+- **Simplicity with gradual complexity:** Approach MetricFlow using familiar data modeling concepts.
+- **Performance and efficiency**: Optimize performance while supporting centralized data engineering and distributed logic ownership.
 
-- It uses YAML files to define a semantic graph, which maps language to data. This graph consists of [semantic models](/docs/build/semantic-models), which serve as data entry points, and [metrics](/docs/build/metrics-overview), which are functions used to create new quantitative indicators.
+<!--MetricFlow is a SQL query generation engine that helps you create metrics by constructing appropriate queries for different granularities and dimensions that are useful for various business applications. 
 
-- MetricFlow is a [BSL package](https://github.com/dbt-labs/metricflow) (code is source available) and available on dbt versions 1.6 and higher. Data practitioners and enthusiasts are highly encouraged to contribute. 
+- It uses YAML files to define a semantic graph, which maps language to data. This graph consists of , which serve as data entry points, and [, which are functions used to create new quantitative indicators.
+
+- MetricFlow is a  () and available on dbt versions 1.6 and higher. 
 
 - MetricFlow, as a part of the dbt Semantic Layer, allows organizations to define company metrics logic through YAML abstractions, as described in the following sections.
 
-- You can install MetricFlow using PyPI as an extension of your [dbt adapter](/docs/supported-data-platforms) in the CLI. To install the adapter, run `pip install "dbt-metricflow[your_adapter_name]"` and add the adapter name at the end of the command. For example, for a Snowflake adapter run `pip install "dbt-metricflow[snowflake]"`.
+- To query metrics dimensions, dimension values, and validate your configurations; install MetricFlow in 
 
-- To query metrics dimensions, dimension values, and validate your configurations; install the [MetricFlow CLI](/docs/build/metricflow-cli).
+MetricFlow has the following principles:
+
+- **Flexible, but complete** &mdash;  Ability to create any metric on any data model by defining logic in flexible abstractions.
+- **Don't Repeat Yourself (DRY)** &mdash; Avoid repetition by allowing metric definitions to be enabled whenever possible.
+- **Simple with progressive complexity** &mdash; Make MetricFlow approachable by relying on known concepts and structures in data modeling. 
+- **Performant and efficient** &mdash; Allow for performance optimizations in centralized data engineering while still enabling distributed definition and ownership of logic.
+-->
 
 ### Semantic graph 
 
@@ -112,8 +130,6 @@ group by 1, 2
 </TabItem>
 <TabItem value="metricflow" label="Calculate with MetricFlow">
 
-> Introducing MetricFlow, a key component of the dbt Semantic Layer 🤩 - simplifying data collaboration and governance.
-
 In the following three example tabs, use MetricFlow to define a semantic model that uses order_total as a metric and a sample schema to create consistent and accurate results &mdash; eliminating confusion, code duplication, and streamlining your workflow.
 
 <Tabs>

website/docs/docs/build/analyses.md

@@ -2,6 +2,7 @@
 title: "Analyses"
 description: "Read this tutorial to learn how to use custom analyses when building in dbt."
 id: "analyses"
+pagination_next: null
 ---
 
 ## Overview