Classifying a Million Snowflake Columns in 9 Days, Solo, with Dagster

A tiered AI classification system was developed in nine days at Group 1001, a financial services company, to automate the classification of data across 62 databases with over a million columns as part of a large migration to a Snowflake account. The system combines deterministic regex rules and Snowflake's native classification tools to label columns effectively and affordably, addressing the challenges of maintaining consistency and accuracy in data governance. Dagster was used for orchestration, enabling a multi-stage pipeline that is legible and maintainable by a single person, even with context switching. The system features a human review workflow and ensures safe corrections through a polling loop, while the orchestration work was streamlined, allowing more focus on the core classification problem. The use of Dagster minimized the need for extensive orchestration code, making the rapid development and deployment possible.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.