User tokens | dbt Developer Hub
User API tokens have been deprecated and will no longer work. Migrate to personal access tokens to resume services.| docs.getdbt.com
User API tokens have been deprecated and will no longer work. Migrate to personal access tokens to resume services.| docs.getdbt.com
Reference public models across dbt projects| docs.getdbt.com
Learn how dbt administrators can use self-service permissions to control access in a dbt Starter account.| docs.getdbt.com
Set up notifications in dbt to receive email or Slack alerts about job run status.| docs.getdbt.com
Use Tableau worksheets to query the dbt Semantic Layer and produce dashboards with trusted date.| docs.getdbt.com
dbt extends functionality across data platforms using multiple dispatch.| docs.getdbt.com
Managing whitespace control| docs.getdbt.com
Quote_columns - Read this in-depth guide to learn about configurations in dbt.| docs.getdbt.com
Constraints are a feature of many data platforms. When specified, the platform will perform additional validation on data as it is being populated in a new table or inserted into a preexisting table. If the validation fails, the table creation or update fails, the operation is rolled back, and you will see a clear error message.| docs.getdbt.com
Learn how dbt administrators can use Snowflake OAuth to control access in a dbt account.| docs.getdbt.com
Learn how dbt administrators can use BigQuery OAuth to control access in a dbt account| docs.getdbt.com
Query metrics and metadata in your dbt project with the MetricFlow commands.| docs.getdbt.com
The `flags` variable contains values of flags provided on the cli.| docs.getdbt.com
Configure hooks to execute SQL before (pre) and after (post) a model is run in dbt.| docs.getdbt.com
The + prefix helps disambiguate between resource paths and configs in dbt_project.yml files.| docs.getdbt.com
Information about data platform connections in dbt Core| docs.getdbt.com
Information about data platform connections| docs.getdbt.com
Implement a CI environment for safe project validation.| docs.getdbt.com
Use custom code from your repository| docs.getdbt.com
Generate and serve the docs for your dbt project.| docs.getdbt.com
Fusion is the next-generation engine for dbt.| docs.getdbt.com
Preparing our atomic building blocks.| docs.getdbt.com
The dbt compile command creates executable SQL from model, test, and analysis files.| docs.getdbt.com
As dbt runs, it generates events. The most common way to see those events is as log messages, written in real time to two places:| docs.getdbt.com
Learn how connecting your GitHub account provides convenience and another layer of security to dbt.| docs.getdbt.com
Learn how to create your own materializations.| docs.getdbt.com
Customize dbt workflows using hooks and operations.| docs.getdbt.com
Learn about Catalog and how to interact with it to understand, improve, and leverage your dbt projects.| docs.getdbt.com
In software engineering, environments are used to enable engineers to develop and test code without impacting the users of their software. Typically, there are two types of environments in dbt:| docs.getdbt.com
Service account tokens help you define permissions for securing access to your dbt account and its projects.| docs.getdbt.com
Use 's capabilities to seamlessly run a dbt job in production or staging environments. Rather than run dbt commands manually from the command line, you can leverage the 's in-app scheduling to automate how and when you execute dbt.| docs.getdbt.com
This overview explains how users are provisioned in via Single Sign-On (SSO).| docs.getdbt.com
Learn how dbt administrators can use licenses and seats to control access in a dbt account.| docs.getdbt.com
Learn how to properly adjust your generate_schema_name() and generate_alias_name() macros.| docs.getdbt.com
Version models to help with lifecycle management| docs.getdbt.com
Different warehouses have different names for logical databases. The information in this document covers "databases" on Snowflake, Redshift, and Postgres; "projects" on BigQuery; and "catalogs" on Databricks Unity Catalog.| docs.getdbt.com
For the test resource type, storefailuresas is an optional config that specifies how test failures should be stored in the database. If storefailures is also configured, storefailuresas takes precedence.| docs.getdbt.com
Model contracts define a set of parameters validated during transformation| docs.getdbt.com
SQL models are the building blocks of your dbt project.| docs.getdbt.com
The dbt platform is the fastest and most reliable way to deploy dbt for scalable data transformation, while dbt Core powers open-source transformation workflows. Together, they provide a seamless analytics engineering experience. Explore our step-by-step guides, quickstart tutorials, and troubleshooting resources to get started with dbt and your data platform.| docs.getdbt.com
Automatically generate project documentation as you run jobs.| docs.getdbt.com
Learn about dbt Labs' product lifecycles.| docs.getdbt.com
Information about the architecture, communication, and security of dbt| docs.getdbt.com
Learn how connecting your GitLab account provides convenience and another layer of security to dbt.| docs.getdbt.com
dbt deps pulls the most recent version of the dependencies listed in your packages.yml from git. See Package-Management for more information.| docs.getdbt.com
Learn about semantic versioning for dbt Core, and how long those versions are supported.| docs.getdbt.com
Configure Python models to enhance your dbt project.| docs.getdbt.com
Learn how to use resource paths to configure resource types in dbt.| docs.getdbt.com
Models properties can be declared in .yml files in your models/ directory (as defined by the model-paths config).| docs.getdbt.com
The dbt run command executes your compiled SQL models against a target database.| docs.getdbt.com
You can manage access to the datasets you're producing with dbt by using grants. To implement these permissions, define grants as resource configs on each model, seed, or snapshot. Define the default grants that apply to the entire project in your dbt_project.yml, and define model-specific grants within each model's SQL or YAML file.| docs.getdbt.com
The `target` variable contains information about your connection to the warehouse.| docs.getdbt.com
Test selection works a little differently from other resource selection. This makes it very easy to:| docs.getdbt.com
About environment-level permissions to protect your information| docs.getdbt.com
Learn how to leverage defer to prod when developing with dbt.| docs.getdbt.com
Learn more about MetricFlow and its key concepts| docs.getdbt.com
Incorporate environment variables using `en_var` function.| docs.getdbt.com
Configure custom schemas for your dbt model's tables and views in the database.| docs.getdbt.com
Reference guide for configuring the dbt_project.yml file.| docs.getdbt.com
Learn how to use source configurations in dbt.| docs.getdbt.com
Use artifacts to power your automated docs site and source freshness data.| docs.getdbt.com
provides a stateful way of deploying dbt. Artifacts are accessible programmatically via the Discovery API in the metadata platform.| docs.getdbt.com
The Discovery API supports ad-hoc queries and integrations. If you are new to the API, refer to About the Discovery API for an introduction.| docs.getdbt.com
Information about single tenant and multi-tenant dbt Cloud instances| docs.getdbt.com
Learn how good documentation for your dbt models helps stakeholders discover and understand your datasets.| docs.getdbt.com
Learn how dbt Cloud administrators can use dbt Cloud's permissioning model to control user-level access in a dbt Cloud account.| docs.getdbt.com
When you define groups in dbt projects, you turn implicit relationships into an explicit grouping.| docs.getdbt.com
Learn how we structure our dbt projects.| docs.getdbt.com
dbt projects have two distinct types of version tags. This field has a different meaning depending on its location.| docs.getdbt.com
Selector methods return all resources that share a common property, using the| docs.getdbt.com
Configure custom aliases to override default naming conventions for models and other resources in dbt.| docs.getdbt.com
The configured test(s) will store their failures when dbt test --store-failures is invoked. If you set this configuration as false but storefailuresas is configured, it will be overridden.| docs.getdbt.com
You can use error thresholds to configure the severity of test results and set when to produce an error or warning based on the number of failed tests.| docs.getdbt.com
When the contract configuration is enforced, dbt will ensure that your model's returned dataset exactly matches the attributes you have defined in yaml, such as name and data_type, as well as any additional constraints supported by the data platform.| docs.getdbt.com
Understand the role of dbt models transforming your data into analytics-ready datasets.| docs.getdbt.com
Learn how to configure and optimize incremental models when developing in dbt.| docs.getdbt.com
Validate that data freshness meets expectations and alert if stale.| docs.getdbt.com
Pass variables from `dbt_project.yml` file into models.| docs.getdbt.com
Read the FAQs to learn more about the dbt Semantic Layer, how it works, how to build metrics, integrations, and more.| docs.getdbt.com
In , both jobs and environments are configured to use a specific version of . The version can be upgraded at any time.| docs.getdbt.com
Integrate and query metrics and dimensions in downstream tools using the Semantic Layer APIs| docs.getdbt.com
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.| docs.getdbt.com
Learn how to trigger a dbt job run when a Git pull request merges.| docs.getdbt.com
How to use dbt commands to set tasks for your dbt Cloud jobs.| docs.getdbt.com
