Visual Data Flow 8. DBT

Table of contents
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dbt Quickstarts
Begin your dbt journey by trying one of our quickstarts, which provides a step-by-step guide to help you set up dbt Cloud or dbt Core with a variety of data platforms.
dbt Cloud
dbt Cloud is a scalable solution that enables you to develop, test, deploy, and explore data products using a single, fully managed software service. It enables teams with diverse skills to build reliable data products at any scale, with capabilities including:
Development experiences tailored to multiple personas (in-browser dbt Cloud IDE or locally with the dbt Cloud CLI)
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The dbt Semantic Layer for consistent metrics that can be delivered to any endpoint
Domain ownership of data with multi-project dbt Mesh setups
dbt Explorer for collaborative data discovery and understanding
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Quickstart for dbt Cloud and Amazon Athena
Integrate dbt Cloud with Amazon Athena for your data transformations.
Quickstart for dbt Cloud and Azure Synapse Analytics
Discover how to integrate dbt Cloud with Azure Synapse Analytics for your data transformations.
Quickstart for dbt Cloud and BigQuery
Discover how to leverage dbt Cloud with BigQuery to streamline your analytics workflows.
Quickstart for dbt Cloud and Databricks
Learn how to integrate dbt Cloud with Databricks for efficient data processing and analysis.
Quickstart for dbt Cloud and Microsoft Fabric
Explore the synergy between dbt Cloud and Microsoft Fabric to optimize your data transformations.
Quickstart for dbt Cloud and Redshift
Learn how to connect dbt Cloud to Redshift for more agile data transformations.
Quickstart for dbt Cloud and Snowflake
Unlock the full potential of using dbt Cloud with Snowflake for your data transformations.
Quickstart for dbt Cloud and Starburst Galaxy
Leverage dbt Cloud with Starburst Galaxy to enhance your data transformation workflows.
Quickstart for dbt Cloud and Teradata
Discover and use dbt Cloud with Teradata to enhance your data transformation workflows.
dbt Core
dbt Core is a command-line open-source tool that enables data practitioners to transform data using analytics engineering best practices. It suits individuals and small technical teams who prefer manual setup and customization, supports community adapters, and open-source standards.
dbt Core from a manual install
Learn how to install dbt Core and set up a project.
dbt Core using GitHub Codespace
Learn how to create a codespace and execute the dbt build command.
Related docs
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Best practices contains information on how dbt Labs approaches building projects through our current viewpoints on structure, style, and setup.
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Last updated on Mar 4, 2025
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