From Raw to Reliable: Build AI-Powered Data Quality Pipelines with Cortex Code

Cortex Code is Snowflake’s AI coding assistant. In this hands-on lab, you’ll see how to move beyond simple code generation and use it as a practical co-pilot for building data quality pipelines end to end.

In this live, hands-on lab, you’ll learn how to:
 

• Use Cortex Code effectively in Snowsight and the CLI with #table grounding, plan mode, specialized skills, and ctx remember for session context.

• Build an AI-powered quality pipeline with AI_EXTRACT, AI_CLASSIFY, AI_SENTIMENT, AI_REDACT, and AI_FILTER to structure, enrich, protect, and de-noise your data.

• Create and attach Data Metric Functions (DMFs) to your tables to continuously monitor nulls, duplicates, freshness, and business rules—so issues are detected before stakeholders notice them.

• Configure Snowflake Notification Integrations and alerts that trigger the moment thresholds are breached, closing the loop from detection to response.

What you’ll leave with
 

• Working Cortex Code snippets you can reuse in your own projects

• A reference data quality pipeline built on Snowflake

• Ready-to-adapt DMF patterns and monitoring setup for your own tables