dbt-labs · matthewshaver · Oct 17, 2023 · Jun 13, 2023 · Jun 15, 2023 · Jul 5, 2023
@@ -3,6 +3,8 @@ 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:

@@ -4,6 +4,8 @@ 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.

@@ -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

@@ -5,6 +5,8 @@ description: "Learn about MetricFlow and build your metrics with semantic models
 sidebar_label: Build your metrics
 tags: [Metrics, Semantic Layer, Governance]
 hide_table_of_contents: true
+pagination_next: "docs/build/sl-getting-started"
+pagination_prev: null
 ---
 
 Use MetricFlow in dbt to centrally define your metrics. As a key component of the [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), MetricFlow is responsible for SQL query construction and defining specifications for dbt semantic models and metrics.

@@ -1,6 +1,7 @@
 ---
 title: "Custom schemas"
 id: "custom-schemas"
+pagination_next: "docs/build/custom-databases"
 ---
 
 By default, all dbt models are built in the schema specified in your target. In dbt projects with lots of models, it may be useful to instead build some models in schemas other than your target schema – this can help logically group models together.

@@ -2,7 +2,7 @@
 title: "Custom target names"
 id: "custom-target-names"
 description: "You can define a custom target name for any dbt Cloud job to correspond to settings in your dbt project."
-
+pagination_next: null
 ---
 
 ## dbt Cloud Scheduler

@@ -2,6 +2,7 @@
 title: "Materializations"
 description: "Read this tutorial to learn how to use materializations when building in dbt."
 id: "materializations"
+pagination_next: "docs/build/incremental-models"
 ---
 
 ## Overview

@@ -4,6 +4,7 @@ id: metrics-overview
 description: "Metrics can be defined in the same or separate YAML files from semantic models within the same dbt project repo."
 sidebar_label: "Creating metrics"
 tags: [Metrics, Semantic Layer]
+pagination_next: "docs/build/cumulative"
 ---
 
 Once you've created your semantic models, it's time to start adding metrics! Metrics can be defined in the same YAML files as your semantic models, or split into separate YAML files into any other subdirectories (provided that these subdirectories are also within the same dbt project repo)

@@ -2,6 +2,8 @@
 title: "About dbt models"
 description: "Read this tutorial to learn how to use models when building in dbt."
 id: "models"
+pagination_next: "docs/build/sql-models"
+pagination_prev: null
 ---
 
 ## Overview

@@ -1,6 +1,7 @@
 ---
 title: "Project variables"
 id: "project-variables"
+pagination_next: "docs/build/environment-variables"
 ---
 
 dbt provides a mechanism, [variables](/reference/dbt-jinja-functions/var), to provide data to models for

@@ -1,6 +1,8 @@
 ---
 title: "About dbt projects"
 id: "projects"
+pagination_next: null
+pagination_prev: null
 ---
 
 A dbt project informs dbt about the context of your project and how to transform your data (build your data sets). By design, dbt enforces the top-level structure of a dbt project such as the `dbt_project.yml` file, the `models` directory, the `snapshots` directory, and so on. Within the directories of the top-level, you can organize your project in any way that meets the needs of your organization and data pipeline.

@@ -6,6 +6,7 @@ keywords:
   - dbt metrics layer
 sidebar_label: Semantic models
 tags: [Metrics, Semantic Layer]
+pagination_next: "docs/build/dimensions"
 ---
 
 Semantic models serve as the foundation for defining data in MetricFlow, which powers the dbt Semantic Layer. You can think of semantic models as nodes in your semantic graph, connected via entities as edges. MetricFlow takes semantic models defined in YAML configuration files as inputs and creates a semantic graph that can be used to query metrics.

@@ -4,6 +4,7 @@ id: simple
 description: "Use simple metrics to directly reference a single measure."
 sidebar_label: Simple
 tags: [Metrics, Semantic Layer]
+pagination_next: null
 ---
 
 Simple metrics are metrics that directly reference a single measure, without any additional measures involved. They are aggregations over a column in your data platform and can be filtered by one or multiple dimensions.

@@ -3,6 +3,8 @@ title: About dbt Cloud setup
 id: about-cloud-setup
 description: "Configuration settings for dbt Cloud."
 sidebar_label: "About dbt Cloud setup"
+pagination_next: "docs/dbt-cloud-environments"
+pagination_prev: null
 ---
 
 dbt Cloud is the fastest and most reliable way to deploy your dbt jobs. It contains a myriad of settings that can be configured by admins, from the necessities (data platform integration) to security enhancements (SSO) and quality-of-life features (RBAC). This portion of our documentation will take you through the various settings found by clicking on the gear icon in the dbt Cloud UI, including:

@@ -4,6 +4,8 @@ id: "dbt-cloud-features"
 sidebar_label: "dbt Cloud features"
 description: "Explore dbt Cloud's features and learn why dbt Cloud is the fastest way to deploy dbt"
 hide_table_of_contents: true
+pagination_next: "docs/cloud/about-cloud/architecture"
+pagination_prev: null
 ---
 
 dbt Cloud is the fastest and most reliable way to deploy dbt. Develop, test, schedule, document, and investigate data models all in one browser-based UI. In addition to providing a hosted architecture for running dbt across your organization, dbt Cloud comes equipped with turnkey support for scheduling jobs, CI/CD, hosting documentation, monitoring & alerting, and an integrated development environment (IDE).

@@ -2,6 +2,7 @@
 title: "Supported browsers"
 id: "browsers"
 description: "dbt Cloud supports the latest browsers like Chrome and Firefox."
+pagination_next: null
 ---
 
 To have the best experience with dbt Cloud, we recommend using the latest versions of the following browsers:

@@ -3,6 +3,8 @@ title: "Billing"
 id: billing 
 description: "dbt Cloud billing information." 
 sidebar_label: Billing
+pagination_next: null
+pagination_prev: null
 ---
 
 dbt Cloud offers a variety of [plans and pricing](https://www.getdbt.com/pricing/) to fit your organization’s needs. With flexible billing options that appeal to large enterprises and small businesses and [server availability](/docs/cloud/about-cloud/regions-ip-addresses) worldwide, dbt Cloud is the fastest and easiest way to begin transforming your data.

@@ -3,6 +3,8 @@ title: "About data platform connections"
 id: about-connections
 description: "Information about data platform connections"
 sidebar_label: "About data platform connections"
+pagination_next: "docs/cloud/connect-data-platform/connect-starburst-trino"
+pagination_prev: null
 ---
 dbt Cloud can connect with a variety of data platform providers including: 
 - [Amazon Redshift](/docs/cloud/connect-data-platform/connect-redshift-postgresql-alloydb) 

@@ -3,6 +3,7 @@ title: "Connect Apache Spark"
 id: connect-apache-spark
 description: "Setup instructions for connecting Apache Spark to dbt Cloud"
 sidebar_label: "Connect Apache Spark"
+pagination_next: null
 ---
 
 <Snippet path="dbt-databricks-for-databricks" />

@@ -3,6 +3,7 @@ title: "Tips and tricks"
 id: dbt-cloud-tips
 description: "Check out any dbt Cloud and IDE-related tips."
 sidebar_label: "Tips and tricks"
+pagination_next: null
 ---
 
 # dbt Cloud tips

@@ -4,6 +4,8 @@ id: develop-in-the-cloud
 description: "Develop, test, run, and build in the Cloud IDE. With the Cloud IDE, you can compile dbt code into SQL and run it against your database directly"
 sidebar_label: Develop in the IDE
 tags: [IDE]
+pagination_next: "docs/cloud/dbt-cloud-ide/ide-user-interface"
+pagination_prev: null
 ---
 
 The dbt Cloud integrated development environment (IDE) is a single interface for building, testing, running, and version-controlling dbt projects from your browser. With the Cloud IDE, you can compile dbt code into SQL and run it against your database directly. 

@@ -3,6 +3,7 @@ title: "Authenticate with Azure DevOps"
 id: "authenticate-azure"
 description: "dbt Cloud developers need to authenticate with Azure DevOps."
 sidebar_label: "Authenticate with Azure DevOps"
+pagination_next: null
 ---
 
 

@@ -1,6 +1,7 @@
 ---
 title: "Connect to Azure DevOps"
 id: "connect-azure-devops"
+pagination_next: "docs/cloud/git/setup-azure"
 ---
 
 <Snippet path="available-enterprise-tier-only" />

@@ -1,6 +1,8 @@
 ---
 title: "Import a project by git URL"
 id: "import-a-project-by-git-url"
+pagination_next: "docs/cloud/git/connect-github"
+pagination_prev: null
 ---
 
 In dbt Cloud, you can import a git repository from any valid git URL that points to a dbt project. There are some important considerations to keep in mind when doing this.

@@ -2,6 +2,8 @@
 title: "About user access in dbt Cloud"
 description: "Learn how dbt Cloud administrators can use dbt Cloud's permissioning model to control user-level access in a dbt Cloud account."
 id: "about-user-access"
+pagination_next: "docs/cloud/manage-access/audit-log"
+pagination_prev: null
 ---
 
 :::info "User access" is not "Model access"

@@ -3,6 +3,8 @@ title: "The audit log for dbt Cloud Enterprise"
 id: audit-log
 description: "You can troubleshoot possible issues and provide security audits by reviewing event activity in your organization."
 sidebar_label: "Audit log"
+pagination_next: null
+pagination_prev: "docs/cloud/manage-access/about-user-access"
 ---
 
 To review actions performed by people in your organization, dbt provides logs of audited user and system events in real time. The audit log appears as events happen and includes details such as who performed the action, what the action was, and when it was performed. You can use these details to troubleshoot access issues, perform security audits, or analyze specific events. 

@@ -3,6 +3,8 @@ title: "Users and licenses"
 description: "Learn how dbt Cloud administrators can use licenses and seats to control access in a dbt Cloud account."
 id: "seats-and-users"
 sidebar: "Users and licenses"
+pagination_next: "docs/cloud/manage-access/self-service-permissions"
+pagination_prev: null
 ---
 
 In dbt Cloud, _licenses_ are used to allocate users to your account. There are three different types of licenses in dbt Cloud:

@@ -3,6 +3,7 @@ title: "Enterprise permissions"
 id: "enterprise-permissions"
 description: "Permission sets for Enterprise plans."
 hide_table_of_contents: true #For the sake of the tables on this page
+pagination_next: null
 ---
 
 import Permissions from '/snippets/_enterprise-permissions-table.md';

@@ -2,6 +2,7 @@
 title: "Set up BigQuery OAuth"
 description: "Learn how dbt Cloud administrators can use licenses and seats to control access in a dbt Cloud account."
 id: "set-up-bigquery-oauth"
+pagination_next: null
 ---
 
 :::info Enterprise Feature

@@ -1,7 +1,8 @@
 ---
-title: "SSO Overview"
+title: "Single sign-on (SSO) Overview"
 id: "sso-overview"
-
+pagination_next: "docs/cloud/manage-access/set-up-sso-saml-2.0"
+pagination_prev: null
 ---
 
 This overview explains how users are provisioned in dbt Cloud via Single Sign-On (SSO).

@@ -3,6 +3,7 @@ title: "Configuring Databricks PrivateLink"
 id: databricks-privatelink
 description: "Configuring PrivateLink for Databricks"
 sidebar_label: "PrivateLink for Databricks"
+pagination_next: null
 ---
 
 The following steps will walk you through the setup of a Databricks AWS PrivateLink endpoint in the dbt Cloud multi-tenant environment.

@@ -3,6 +3,8 @@ title: "Configuring IP restrictions"
 id: ip-restrictions
 description: "Configuring IP restrictions to outside traffic from accessing your dbt Cloud environment"
 sidebar_label: "IP restrictions"
+pagination_next: "docs/cloud/secure/about-privatelink"
+pagination_prev: null
 ---
 
 import SetUpPages from '/snippets/_available-tiers-iprestrictions.md';

@@ -2,6 +2,7 @@
 title: "Build and view your docs with dbt Cloud"
 id: "build-and-view-your-docs"
 description: "Automatically generate project documentation as you run jobs."
+pagination_next: null
 ---
 
 dbt enables you to generate documentation for your project and data warehouse, and renders the documentation in a website. For more information, see [Documentation](/docs/collaborate/documentation).

@@ -2,6 +2,8 @@
 title: "About documentation"
 description: "Learn how good documentation for your dbt models helps stakeholders discover and understand your datasets."
 id: "documentation"
+pagination_next: "docs/collaborate/build-and-view-your-docs"
+pagination_prev: null
 ---
 
 ## Related documentation

@@ -2,6 +2,8 @@
 title: "Explore your dbt projects (beta)"
 sidebar_label: "Explore dbt projects (beta)"
 description: "Learn about dbt Explorer and how to interact with it to understand, improve, and leverage your data pipelines."
+pagination_next: null
+pagination_prev: null
 ---
 
 With dbt Explorer, you can view your project's [resources](/docs/build/projects) (such as models, tests, and metrics) and their <Term id="data-lineage">lineage</Term> to gain a better understanding of its latest production state. Navigate and manage your projects within dbt Cloud to help your data consumers discover and leverage your dbt resources.

@@ -3,6 +3,8 @@ title: "About git"
 id: git-version-control
 description: "Git overview"
 sidebar_label: "About git"
+pagination_next: "docs/collaborate/git/version-control-basics"
+pagination_prev: null
 ---
 
 A [version control](https://en.wikipedia.org/wiki/Version_control) system allows you and your teammates to work collaboratively, safely, and simultaneously on a single project. Version control helps you track all the code changes made in your dbt project.

@@ -1,6 +1,7 @@
 ---
 title: "Merge conflicts"
 id: "merge-conflicts"
+pagination_next: null
 ---
 
 [Merge conflicts](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/addressing-merge-conflicts/about-merge-conflicts) in the [dbt Cloud IDE](/docs/cloud/dbt-cloud-ide/develop-in-the-cloud) often occur when multiple users are simultaneously making edits to the same section in the same file. This makes it difficult for Git to decide what changes to incorporate in the final merge.  

@@ -2,6 +2,8 @@
 title: "About model governance"
 id: about-model-governance
 description: "Information about new features related to model governance"
+pagination_next: "docs/collaborate/govern/model-access"
+pagination_prev: null
 ---
 <VersionBlock lastVersion="1.5">
 

@@ -3,6 +3,7 @@ title: "Project dependencies"
 id: project-dependencies
 sidebar_label: "Project dependencies"
 description: "Reference public models across dbt projects"
+pagination_next: null
 ---
 
 :::caution Closed Beta - dbt Cloud Enterprise

@@ -1,6 +1,7 @@
 ---
 title: "Contribute to adapters"
 id: "contribute-core-adapters"
+pagination_next: null
 ---
 
 The dbt Community exists to allow analytics practitioners share their knowledge, help others and collectively to drive forward the discipline of analytics engineering. There are opportunities here for everyone to contribute whether you're at the beginning your analytics engineering journey or you are a seasoned data professional.

@@ -3,6 +3,8 @@ 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-the-cli"
+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.

@@ -4,6 +4,8 @@ id: "about-core-connections"
 description: "Information about data platform connections in dbt Core"
 sidebar_label: "About data platform connections in dbt Core"
 hide_table_of_contents: true
+pagination_next: "docs/core/connect-data-platform/profiles.yml"
+pagination_prev: null
 ---
 
 dbt Core can connect with a variety of data platform providers including: 

@@ -14,6 +14,7 @@ meta:
   slack_channel_link: 'https://join.slack.com/t/upsolvercommunity/shared_invite/zt-1zo1dbyys-hj28WfaZvMh4Z4Id3OkkhA'
   platform_name: 'Upsolver'
   config_page: '/reference/resource-configs/upsolver-configs'
+pagination_next: null
 ---
 
 <h2> Overview of {frontMatter.meta.pypi_package} </h2>

@@ -1,6 +1,7 @@
 ---
 title: "dbt Core environments"
 id: "dbt-core-environments"
+pagination_next: "docs/running-a-dbt-project/run-your-dbt-projects"
 ---
 
 dbt makes it easy to maintain separate production and development environments through the use of [targets](/reference/dbt-jinja-functions/target.md) within a [profile](/docs/core/connect-data-platform/profiles.yml). A typical profile, when using dbt locally (for example, running from your command line), will have a target named `dev` and have this set as the default. This means that while making changes, your objects will be built in your _development_ target without affecting production queries made by your end users. Once you are confident in your changes, you can deploy the code to _production_, by running your dbt project with a _prod_ target.

@@ -2,6 +2,8 @@
 title: "About installing dbt"
 id: "installation"
 description: "You can install dbt Core using a few different tested methods."
+pagination_next: "docs/core/homebrew-install"
+pagination_prev: null
 ---
 
 You can install dbt Core on the command line by using one of these methods:

@@ -1,6 +1,7 @@
 ---
 title: "Install from source"
 description: "You can install dbt Core from its GitHub code source."
+pagination_next: null
 ---
 
 dbt Core and almost all of its adapter plugins are open source software. As such, the codebases are freely available to download and build from source. You might install from source if you want the latest code or want to install dbt from a specific commit. This might be helpful when you are contributing changes, or if you want to debug a past change.