+Access and use the dbt Cloud visual editor to create or edit dbt models through a visual, drag-and-drop experience. Use the built-in AI for custom code generation in your development experience. +
+ +:::tip Beta feature +The visual editor provides users with a seamless and drag-and-drop experience inside of dbt Cloud. It's available in private beta for [dbt Cloud Enterprise accounts](https://www.getdbt.com/pricing). + +To join the private beta, [register your interest](https://docs.google.com/forms/d/e/1FAIpQLScPjRGyrtgfmdY919Pf3kgqI5E95xxPXz-8JoVruw-L9jVtxg/viewform) or reach out to your account team to begin this process. +::: + +## Prerequisites +- You have a [dbt Cloud Enterprise](https://www.getdbt.com/pricing) account +- You have a [developer license](/docs/cloud/manage-access/seats-and-users) with developer credentials set up +- You have an existing dbt Cloud project already created +- You are [Keep on latest](/docs/dbt-versions/upgrade-dbt-version-in-cloud#keep-on-latest-version) for a versionless experience +- Successful job run on Production or Staging [environment](/docs/dbt-cloud-environments) +- Have AI-powered features toggle enabled + +## Access visual editor + +Before accessing the editor, you should have a dbt Cloud project already set up. This includes a Git repository, data platform connection, environments, and developer credentials. If you don't have this set up, please contact your dbt Cloud Admin. + +To access the visual editor: +- Type in the following URL, replacing the ACCOUNT_ID and ENVIRONMENT_ID with your own account and environment ID: `https://ACCESS_URL/visual-editor/ACCOUNT_ID/env/ENVIRONMENT_ID/` + - The environment ID must have had runs that generated catalogs in it. + +- For example, if my region is North America multi-tenant, account ID is 10, environment ID with a generated catalog run is 100, my URL should be: + + - `https://cloud.getdbt.com/visual-editor/10/env/100/` + ++The visual editor interface contains an operator toolbar, operators, canvas, built-in AI, and more to help you create dbt models through a seamless drag-and-drop experience in dbt Cloud. +
+ +:::tip Beta feature +The visual editor provides users with a seamless and visual, drag-and-drop experience inside dbt Cloud. It's available in private beta for [dbt Cloud Enterprise accounts](https://www.getdbt.com/pricing). + +To join the private beta, [register your interest](https://docs.google.com/forms/d/e/1FAIpQLScPjRGyrtgfmdY919Pf3kgqI5E95xxPXz-8JoVruw-L9jVtxg/viewform) or reach out to your account team to begin this process. +::: + +This page offers comprehensive definitions and terminology of user interface elements, allowing you to navigate the dbt Cloud visual editor landscape with ease. + +The visual editor interface is composed of: + +- **Operator toolbar** — Located at the top of the interface, the toolbar displays all the nodes available. Use the toggle on the left of the toolbar to display or hide it. +- **Operators** — perform specific transformations or configurations (such as model, join, aggregate, filter, and so on). Use connectors to link the operators and build a complete data transformation pipeline. +- **Canvas** — The main whiteboard space below the node toolbar. The canvas allows you to create or modify models through a sleek drag-and-drop experience. +- **Configuration panel** — Each operator has a configuration panel that opens when you click on it. The configuration panel allows you to configure the operator, review the current model, preview changes to the table, view the SQL code for the node, and delete the operator. + +## Operators + +The operator toolbar above the canvas contains the different transformation operators available to use. Use each operator to configure or perform specific tasks, like adding filters or joining models by dragging an operator onto the canvas. You can connect operators using the connector line, which allows you to form a complete dbt model for your data transformation. + ++The dbt Cloud visual editor helps analysts quickly create, edit, and visualize dbt models through a visual, drag-and-drop experience and with a built-in AI for custom code generation. +
+ +:::tip Beta feature +The visual editor in dbt Cloud provides users with a seamless and visual, drag-and-drop experience inside dbt Cloud. It's available in private beta for [dbt Cloud Enterprise accounts](https://www.getdbt.com/pricing). + +To join the private beta, [register your interest](https://docs.google.com/forms/d/e/1FAIpQLScPjRGyrtgfmdY919Pf3kgqI5E95xxPXz-8JoVruw-L9jVtxg/viewform) or reach out to your account team to begin this process. +::: + +The visual editor allows organizations to enjoy the many benefits of code-driven development—such as increased precision, ease of debugging, and ease of validation — while retaining the flexibility to have different contributors develop wherever they are most comfortable. Users can also take advantage of built-in AI for custom code generation, making it an end-to-end frictionless experience. + +These models compile directly to SQL and are indistinguishable from other dbt models in your projects: +- Visual models are version-controlled in your backing Git provider. +- All models are accessible across projects in [dbt Mesh](/best-practices/how-we-mesh/mesh-1-intro). +- Models can be materialized into production through [dbt Cloud orchestration](/docs/deploy/deployments), or be built directly into a user's development schema. +- Integrate with [dbt Explorer](/docs/collaborate/explore-projects) and the [dbt Cloud IDE](/docs/cloud/dbt-cloud-ide/develop-in-the-cloud). + +=){B*CVv(sx7
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