Real time Snowflake ETL + Interview Scenario | Load Valid Data & Auto Send failure records to Client
Automatically Handle Failed Records in Snowflake and Send Back to Clients via AWS S3!
In this video, we dive deep into a real-time Snowflake data pipeline scenario where clients upload files to AWS S3, and we automate the process of:
✅ Loading valid records into the target Snowflake table
❌ Capturing invalid (faulty) records during the COPY INTO operation
Sending those faulty records back to the client through an S3 rejected folder
We explore key Snowflake features that make this automation possible:
🔍 What You’ll Learn:
How to use VALIDATION_MODE in the COPY INTO command to preview errors before loading
How the VALIDATE() table function helps identify all failure records
⚠️ Important tips and gotchas to remember when using VALIDATE() effectively
How to write a Snowflake Stored Procedure (SP) to automate:
Loading valid data
Capturing invalid data
Writing rejected records back to S3 for client reference
This is a must-watch tutorial for anyone working with data pipelines, Snowflake automation, and real-time file processing with S3.
This video is based on an actual client scenario where data quality and automated feedback loops were crucial to the process.
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