Preparing our atomic building blocks.| docs.getdbt.com
Reflections on bringing the ELT game to the lake| Giacomo Coletto
SQL models are the building blocks of your dbt project.| 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
Selector methods return all resources that share a common property, using the| docs.getdbt.com
Validate that data freshness meets expectations and alert if stale.| docs.getdbt.com
Use this guide to build and define metrics, set up the dbt Cloud Semantic Layer, and query them using Google Sheets.| docs.getdbt.com
This page explains the difference between properties and configurations in dbt.| docs.getdbt.com
The dbt source command provides subcommands that are useful when working with source data. This command provides one subcommand, dbt source freshness.| docs.getdbt.com
With the Discovery API, you can query the metadata in dbt Cloud to learn more about your dbt deployments and the data it generates to analyze them and make improvements.| docs.getdbt.com
Configure dbt data tests to assess the quality of your input data and ensure accuracy in resulting datasets.| docs.getdbt.com
This page contains the collective wisdom of experienced users of on how to best use it in your analytics work. Observing these best practices will help your analytics team work as effectively as possible, while implementing the pro-tips will add some polish to your projects!| docs.getdbt.com
A guide to how to start and evolve a dbt project.| docs.getdbt.com
The dbt_project_evaluator is a dbt package created by the Professional Services team at dbt Labs to help analytics engineers automatically audit their dbt projects for bad practices. Goodbye auditing nightmares, hello beautiful DAG.| docs.getdbt.com