LLM-powered ETL: Snowflake’s Leap into Data Warehouse AI
The Future of ETL is Here
The modern Data Engineering space has been marked by incredibly rapid product innovations that test and expand the diagram of the “Modern Data Stack”. The newest tidal wave to wash the data shores is what I call the ETL-LLM.
ETL-LLM is exactly what it sounds like. LLMs, specifically Generative AI, applied to ETL/ELT pipelines. The benefits here range from accelerating/automatic manual workflows to performance boosts for key KPIs.
In fact, some can say this revolution is already here. Data Observability tools like Fiddler AI is now brandishing their AI observability functionalities. Data Lineage companies have quickly pivoted to AI to stay ahead of the product and marketing curve.
Snowflake’s entrance to LLMs in ETL workflow is far more expansive. It is no secret that Snowflake has been the top of class Data Warehousing solution in the market. Always has been. But now, Snowflake is taking one giant step further by enabling customers to bake in AI calls into its core data products. The innovation here is to seamless blend Data Science into Data Engineering workloads in order to super charge the latter.
This is what we call Data Warehousing AI, or ETL-LLM.
