# Snowflake workflow
URL: https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/ai-integrations-platforms/ml-snowflake.html

> Work with Snowflake and DataRobot's Python client to import data, build and evaluate models, and deploy a model into production to make new predictions.

# Snowflake workflow

[Access this AI accelerator on GitHub](https://github.com/datarobot-community/ai-accelerators/tree/main/ecosystem_integration_templates/Snowflake_template/Snowflake%20-%20End-to-end%20Ecommerce%20Churn.ipynb)

This AI accelerator walks through how to work with Snowflake (as a data source) and DataRobot's Python client to import data, build and evaluate models, and deploy a model into production to make new predictions. More broadly, the DataRobot API is a critical tool for data scientists to accelerate their machine learning projects with automation while integrating the platform's capabilities into their code-first workflows and coding environments of choice.

By using this accelerator, you will:

- Connect to DataRobot.
- Import data from Snowflake into DataRobot.
- Create a DataRobot project and run Autopilot.
- Select and evaluate the top performing model.
- Deploy the recommended model with MLOps model monitoring.
- Orchestrate scheduled batch predictions that write results back to Snowflake.

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