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Getting Started dbt in Datacoves

What you will learn

💡 How to streamline the process of creating new sources and models in dbt using dbt coves, eliminating the need for manual SQL and YAML file creation.

⚙️ Running the generate sources command to automatically create directory structures, SQL models, and source YAML files, including flattening variant columns when necessary.

🖥 Exploring various methods to execute models, from using right-click options, the run button, or keyboard shortcuts, for efficient workflow management.

🔍 Using accelerators such as autocomplete for functions like source and ref to speed up coding and ensure accuracy.

📊 Using linting, command-enter previews, and dbt compile functions to catch errors and debug SQL, while adhering to best practices.

🧪 Running and managing tests associated with models through various testing options available in the dbt interface and power user extensions.

Speakers

Mayra Peña
Data Engineering | Technical Customer Success

End-to-end data analytics with Managed dbt and Airflow

Don’t let platform limitations or maintenance overhead hold you back.

Noel gomez

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Datacoves is an enterprise DataOps platform with Managed dbt and Airflow for data transformation and orchestration, as well as VS Code in the browser for development

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