Merge branch 'current' into patch-1

website/docs/docs/about-setup.md

@@ -21,14 +21,14 @@ 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, how to use the IDE, and how to install the dbt Cloud CLI."
+    body="Learn how to connect to a data platform, integrate with secure authentication methods, and configure a sync with a git repo."
     link="/docs/cloud/about-cloud-setup"
     icon="dbt-bit"/>
 
 <Card
-    title="dbt Core installation"
-    body="Learn how to connect install dbt Core using Pip, Homebrew, Docker, or the open source repo."
-    link="/docs/core/installation"
+    title="dbt Core setup"
+    body="Learn about dbt Core and how to setup data platform connections."
+    link="/docs/core/about-core-setup"
     icon="dbt-bit"/>
 
 </div>

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

@@ -14,7 +14,7 @@ Use MetricFlow in dbt to centrally define your metrics. As a key component of th
 
 MetricFlow allows you to:
 - Intuitively define metrics in your dbt project
-- Develop from your preferred environment, whether that's the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation), [dbt Cloud IDE](/docs/cloud/dbt-cloud-ide/develop-in-the-cloud), or [dbt Core](/docs/core/installation)
+- Develop from your preferred environment, whether that's the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation), [dbt Cloud IDE](/docs/cloud/dbt-cloud-ide/develop-in-the-cloud), or [dbt Core](/docs/core/installation-overview)
 - Use [MetricFlow commands](/docs/build/metricflow-commands) to query and test those metrics in your development environment 
 - Harness the true magic of the universal dbt Semantic Layer and dynamically query these metrics in downstream tools (Available for dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) accounts only).
 

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

@@ -8,7 +8,7 @@ tags: [Metrics, Semantic Layer]
 
 Once you define metrics in your dbt project, you can query metrics, dimensions, and dimension values, and validate your configs using the MetricFlow commands. 
 
-MetricFlow allows you to define and query metrics in your dbt project in the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation), [dbt Cloud IDE](/docs/cloud/dbt-cloud-ide/develop-in-the-cloud), or [dbt Core](/docs/core/installation). To experience the power of the universal [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) and dynamically query those metrics in downstream tools, you'll need a dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) account. 
+MetricFlow allows you to define and query metrics in your dbt project in the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation), [dbt Cloud IDE](/docs/cloud/dbt-cloud-ide/develop-in-the-cloud), or [dbt Core](/docs/core/installation-overview). To experience the power of the universal [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) and dynamically query those metrics in downstream tools, you'll need a dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) account. 
 
 MetricFlow is compatible with Python versions 3.8, 3.9, 3.10, and 3.11.
 

website/docs/docs/build/packages.md

@@ -25,15 +25,9 @@ dbt _packages_ are in fact standalone dbt projects, with models and macros that
 * It's important to note that defining and installing dbt packages is different from [defining and installing Python packages](/docs/build/python-models#using-pypi-packages)
 
 
-:::info `dependencies.yml` has replaced `packages.yml`
-Starting from dbt v1.6, `dependencies.yml` has replaced `packages.yml`. This file can now contain both types of dependencies: "package" and "project" dependencies.
-- "Package" dependencies lets you add source code from someone else's dbt project into your own, like a library. 
-- "Project" dependencies provide a different way to build on top of someone else's work in dbt. Refer to [Project dependencies](/docs/collaborate/govern/project-dependencies) for more info.
-- 
-You can rename `packages.yml` to `dependencies.yml`, _unless_ you need to use Jinja within your packages specification. This could be necessary, for example, if you want to add an environment variable with a git token in a private git package specification.
-
-:::
+import UseCaseInfo from '/snippets/_packages_or_dependencies.md';
 
+<UseCaseInfo/>
 
 ## How do I add a package to my project?
 1. Add a file named <VersionBlock firstVersion="1.6"> `dependencies.yml` or </VersionBlock> `packages.yml` to your dbt project. This should be at the same level as your `dbt_project.yml` file.

website/docs/docs/cloud/about-cloud-setup.md

@@ -13,14 +13,13 @@ dbt Cloud is the fastest and most reliable way to deploy your dbt jobs. It conta
 - Configuring access to [GitHub](/docs/cloud/git/connect-github), [GitLab](/docs/cloud/git/connect-gitlab), or your own [git repo URL](/docs/cloud/git/import-a-project-by-git-url).
 - [Managing users and licenses](/docs/cloud/manage-access/seats-and-users)
 - [Configuring secure access](/docs/cloud/manage-access/about-user-access)
-- Configuring the [dbt Cloud IDE](/docs/cloud/about-cloud-develop)
-- Installing and configuring the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation)
 
 These settings are intended for dbt Cloud administrators. If you need a more detailed first-time setup guide for specific data platforms, read our [quickstart guides](/guides).
 
 If you want a more in-depth learning experience, we recommend taking the dbt Fundamentals on our [dbt Learn online courses site](https://courses.getdbt.com/).
 
 ## Prerequisites
+
 - To set up dbt Cloud, you'll need to have a dbt Cloud account with administrator access. If you still need to create a dbt Cloud account, [sign up today](https://getdbt.com) on our North American servers or [contact us](https://getdbt.com/contact) for international options.
 - To have the best experience using dbt Cloud, we recommend you use modern and up-to-date web browsers like Chrome, Safari, Edge, and Firefox.
 

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

@@ -0,0 +1,30 @@
+---
+title: About developing in dbt
+id: about-develop-dbt
+description: "Learn how to develop your dbt projects using dbt Cloud."
+sidebar_label: "About developing in dbt" 
+pagination_next: "docs/cloud/about-cloud-develop-defer"
+hide_table_of_contents: true
+---
+
+Develop dbt projects using dbt Cloud, which offers a fast and reliable way to work on your dbt project. It runs dbt Core in a hosted (single or multi-tenant) environment.
+
+You can develop in your browser using an integrated development environment (IDE) or in a dbt Cloud-powered command line interface (CLI).
+
+<div className="grid--2-col" >
+
+<Card
+    title="dbt Cloud CLI"
+    body="Allows you to develop and run dbt commands from your local command line or code editor against your dbt Cloud development environment."
+    link="/docs/cloud/cloud-cli-installation"
+    icon="dbt-bit"/>
+
+  <Card
+    title="dbt Cloud IDE"
+    body="Develop directly in your browser, making dbt project development efficient by compiling code into SQL and managing project changes seamlessly using an intuitive user interface."
+    link="/docs/cloud/dbt-cloud-ide/develop-in-the-cloud"
+    icon="dbt-bit"/>
+
+</div><br />
+
+To get started with dbt development, you'll need a [dbt Cloud](https://www.getdbt.com/signup) account and developer seat. For a more comprehensive guide about developing in dbt, refer to our [quickstart guides](/guides).

website/docs/docs/collaborate/govern/project-dependencies.md

@@ -22,8 +22,12 @@ This year, dbt Labs is introducing an expanded notion of `dependencies` across m
 - **Packages** — Familiar and pre-existing type of dependency. You take this dependency by installing the package's full source code (like a software library).
 - **Projects** — A _new_ way to take a dependency on another project. Using a metadata service that runs behind the scenes, dbt Cloud resolves references on-the-fly to public models defined in other projects. You don't need to parse or run those upstream models yourself. Instead, you treat your dependency on those models as an API that returns a dataset. The maintainer of the public model is responsible for guaranteeing its quality and stability.
 
+import UseCaseInfo from '/snippets/_packages_or_dependencies.md';
+
+<UseCaseInfo/>
+
+Refer to the [FAQs](#faqs) for more info.
 
-Starting in dbt v1.6 or higher, `packages.yml` has been renamed to `dependencies.yml`. However, if you need use Jinja within your packages config, such as an environment variable for your private package, you need to keep using `packages.yml` for your packages for now. Refer to the [FAQs](#faqs) for more info.
 
 ## Prerequisites
 
@@ -33,22 +37,6 @@ In order to add project dependencies and resolve cross-project `ref`, you must:
 - Have a successful run of the upstream ("producer") project
 - Have a multi-tenant or single-tenant [dbt Cloud Enterprise](https://www.getdbt.com/pricing) account (Azure ST is not supported but coming soon)
 
-<!-- commenting out in case we can repurpose content
-### About dependencies.yml
-
-There are some important differences between using a `dependencies.yml` compared to a `packages.yml` file:
-
-- `dependencies.yml`
-  - Primarily designed for dbt Mesh and cross-project reference workflow.
-  - Supports both Projects and non-private dbt packages (private packages aren't supported yet).
-  - Helps maintain your project's organization by allowing you to specify hub packages like `dbt_utils`, reducing the need for multiple YAML files.
-  - Does not support conditional configuration using Jinja-in-yaml 
-
-- `packages.yml`
-  - Does not contribute to the dbt Mesh workflow.
-  - Serves as a list of dbt Packages (such as dbt projects) that you want to download into your root or parent dbt project.
-  - Can only include packages, including private packages (doesn't support Projects)
--->
 ## Example
 
 As an example, let's say you work on the Marketing team at the Jaffle Shop. The name of your team's project is `jaffle_marketing`:

website/docs/docs/connect-adapters.md

@@ -15,7 +15,7 @@ Explore the fastest and most reliable way to deploy dbt using dbt Cloud, a hoste
 
 Install dbt Core, an open-source tool, locally using the command line. dbt communicates with a number of different data platforms by using a dedicated  adapter plugin for each. When you install dbt Core, you'll also need to install the specific adapter for your database, [connect to dbt Core](/docs/core/about-core-setup), and set up a `profiles.yml` file.
 
-With a few exceptions [^1], you can install all [Verified adapters](/docs/supported-data-platforms) from PyPI using `python -m pip install adapter-name`. For example to install Snowflake, use the command `python -m pip install dbt-snowflake`. The installation will include `dbt-core` and any other required dependencies, which may include both other dependencies and even other adapter plugins. Read more about [installing dbt](/docs/core/installation).
+With a few exceptions [^1], you can install all [Verified adapters](/docs/supported-data-platforms) from PyPI using `python -m pip install adapter-name`. For example to install Snowflake, use the command `python -m pip install dbt-snowflake`. The installation will include `dbt-core` and any other required dependencies, which may include both other dependencies and even other adapter plugins. Read more about [installing dbt](/docs/core/installation-overview).
 
 [^1]: Here are the two different adapters. Use the PyPI package name when installing with `pip`
 

website/docs/docs/core/about-core-setup.md

@@ -3,17 +3,18 @@ title: About dbt Core setup
 id: about-core-setup
 description: "Configuration settings for dbt Core."
 sidebar_label: "About dbt Core setup"
-pagination_next: "docs/core/about-dbt-core"
+pagination_next: "docs/core/dbt-core-environments"
 pagination_prev: null
 ---
 
 dbt Core is an [open-source](https://github.com/dbt-labs/dbt-core) tool that enables data teams to transform data using analytics engineering best practices. You can install dbt locally in your environment and use dbt Core on the command line. It can communicate with databases through adapters.
 
  This section of our docs will guide you through various settings to get started:
 
-- [About dbt Core](/docs/core/about-dbt-core)
-- [Installing dbt](/docs/core/installation)
 - [Connecting to a data platform](/docs/core/connect-data-platform/profiles.yml)
 - [How to run your dbt projects](/docs/running-a-dbt-project/run-your-dbt-projects)
 
+To learn about developing dbt projects in dbt Cloud or dbt Core, refer to [Develop dbt](/docs/cloud/about-develop-dbt).
+- **Note** — dbt Cloud provides a command line interface with the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation). Both the open-sourced dbt Core and the dbt Cloud CLI are command line tools that let you run dbt commands. The key distinction is the dbt Cloud CLI is tailored for dbt Cloud's infrastructure and integrates with all its [features](/docs/cloud/about-cloud/dbt-cloud-features).
+
 If you need a more detailed first-time setup guide for specific data platforms, read our [quickstart guides](https://docs.getdbt.com/guides).

website/docs/docs/core/connect-data-platform/profiles.yml.md

@@ -3,7 +3,7 @@ title: "About profiles.yml"
 id: profiles.yml
 ---
 
-If you're using [dbt Core](/docs/core/about-dbt-core), you'll need a `profiles.yml` file that contains the connection details for your data platform. When you run dbt Core from the command line, it reads your `dbt_project.yml` file to find the `profile` name, and then looks for a profile with the same name in your `profiles.yml` file. This profile contains all the information dbt needs to connect to your data platform. 
+If you're using [dbt Core](/docs/core/installation-overview), you'll need a `profiles.yml` file that contains the connection details for your data platform. When you run dbt Core from the command line, it reads your `dbt_project.yml` file to find the `profile` name, and then looks for a profile with the same name in your `profiles.yml` file. This profile contains all the information dbt needs to connect to your data platform. 
 
 For detailed info, you can refer to the [Connection profiles](/docs/core/connect-data-platform/connection-profiles).
 

website/docs/docs/core/docker-install.md

@@ -11,7 +11,7 @@ You might also be able to use Docker to install and develop locally if you don't
 
 ### Prerequisites
 * You've installed Docker. For more information, see the [Docker](https://docs.docker.com/) site.
-* You understand which database adapter(s) you need. For more information, see [About dbt adapters](/docs/core/installation#about-dbt-adapters).
+* You understand which database adapter(s) you need. For more information, see [About dbt adapters](docs/core/installation-overview#about-dbt-data-platforms-and-adapters).
 * You understand how dbt Core is versioned. For more information, see [About dbt Core versions](/docs/dbt-versions/core).
 * You have a general understanding of the dbt, dbt workflow, developing locally in the command line interface (CLI). For more information, see [About dbt](/docs/introduction#how-do-i-use-dbt).