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Snowflake and Prefect: Architecture Built for Production
The fastest and most secure way to deploy workflows to production while retaining full visibility into data quality.
Standardize Snowflake Usage
Orchestrate all your data into Snowflake from Prefect to ensure consistency and traceability of your data pipelines. Whether you're using dbt or an event-driven workflow, Prefect makes all task dependencies explicit.
1from prefect_dbt_flow import dbt_flow
2from prefect_dbt_flow.dbt import DbtProfile, DbtProject
3
4my_flow = dbt_flow(
5 project=DbtProject(
6 name="jaffle_shop",
7 project_dir="jaffle_shop/",
8 profiles_dir="jaffle_shop/",
9 ),
10 profile=DbtProfile(
11 target="dev"
12 )
13)
14
15if __name__ == "__main__":
16 my_flow()Supporting Business Critical Data at Crumbl
Chandler Soto, Data Engineer at Crumbl, supports various models for forecasting at Crumbl, a $1B business. The business critical function has confidence because of the visibility they gain with Prefect into their Snowflake data.
More Reading
Read about how you can scale your scheduled and event-driven critical data pipelines with Prefect and Snowflake.
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