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Available for Enterprise Edition only.
In Prophecy, a model comprises a set of gems that process data into one output. In other words, each model corresponds to a single table in your database. Models leverage the dbt build system and can run on either SQL fabrics or Prophecy fabrics. To work with the dbt build, Prophecy saves each visual model as a SQL file in your project repository in Git. Prophecy’s visual interface supports SQL models only; if you’d like to define Python models, you must do so using the code interface.

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Create models

To add a new model to your project:
  1. Open your project in the project editor.
  2. Click + Add Entity from the bottom of the Project tab in the left sidebar.
  3. Click Model.
  4. In the Add Model dialog, add a Model Name.
  5. Review the path where the model will be saved in the project repository. In most cases, the default model path is sufficient.
  6. Click Create.
This opens a new model canvas that is prepopulated with a target model. Note that the dbt framework restricts models to one target output.
While you can develop models visually using gems, you can also write models directly in the code view, which is automatically synced with the visual view.

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Compatible gems

Each gem in a model maps to a SQL statement. As you configure gems on the visual canvas, Prophecy automatically generates the corresponding SQL, determines whether to use a CTE or subquery for each step, and integrates your changes into the overall model.

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Advanced settings

The Advanced Settings dialog lets you set dbt configurations at the project, folder, or model level. Each setting corresponds to standard dbt configurations, typically defined in a dbt project YAML file. They cover properties such as materialization behavior, physical storage, metadata, and access controls. Some settings reflect properties found in the target model gem. When you update a setting through the Advanced Settings panel, it automatically syncs with the corresponding target model gem when relevant. To open the Advanced Settings:
  1. Open the project settings menu beside the project name.
  2. Select Advanced Settings.
  3. Choose to edit the Project Settings, Folder Settings, or Model Settings.
Advanced Settings
Folder Settings only apply to directories that contain models.

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Schedule models

To schedule automated model execution:

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Models vs pipelines

Models and pipelines are two different SQL project components. The following table describes the key differences between models and pipelines.

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Show underlying models

Many visual transformations in pipelines are compiled into models under the hood. If you are working on a pipeline, you can view and edit the code of underlying dbt models in a pipeline. However, you cannot visually edit these underlying models. To view these models, select Show Models from the project interface. Show Models