Airflow and dbt Cloud
Introduction
Introduction
Learn the benefits of version-controlled analytics code and custom pipelines in dbt for enhanced code testing and workflow automation during the development process.
Learn about errors and the art of debugging them.
Implement a CI environment for safe project validation.
Learn how to migrate from dbt-spark to dbt-databricks.
Learn how to move from dbt Core to dbt Cloud and what you need to get started.
Use this guide to learn how to optimize your dbt Cloud experience and get answers to common questions.
Use this guide to understand the considerations and methods you need to move from dbt Core to dbt Cloud.
Learn more about optimizing and troubleshooting your dbt models on Databricks
Learn how to deliver models to end users and use best practices to maintain production data.
Introduction
Introduction
Introduction
Introduction
Introduction
Introduction
Introduction
Use this guide to build and define metrics, set up the dbt Cloud Semantic Layer, and query them using Google Sheets.
Introduction
Learn more about setting up your dbt project with Databricks.
Learn how to use Databricks workflows to run dbt Cloud jobs