Snowflake Cortex is basically Snowflake’s way of saying, “Hey, we do AI now!” It’s a fully managed service that brings machine learning and generative AI right into your Snowflake environment. So instead of shipping your data out to some other service for analysis, you can just do the smart stuff right there, right where your data already lives.
This means faster insights, fewer headaches, and no more jumping between tools or writing messy data pipelines just to make predictions or run an LLM.
How To Use Snowflake Cortex (The Easy Way)
Let’s get hands-on. Here’s a super basic example of how to use Cortex to generate text from a prompt using an LLM (Large Language Model).
Step 1: Make Sure You’ve Got Access
You’ll need to be on a Snowflake account with Cortex enabled (some features may be in preview). Check with your admin if you’re unsure.
Step 2: Use the Built-In Function
Snowflake Cortex provides SQL functions like AI_GENERATE_TEXT() to interact with LLMs. Here’s a fun example:
SELECT AI_GENERATE_TEXT(
‘Write a haiku about data warehouses.’
) AS haiku;
Boom. Instant poetry, courtesy of AI — and it ran directly in your Snowflake worksheet.
Step 3: Try More Use Cases
You’re not limited to haikus (though they’re cool). Try:
- Summarizing customer feedback
- Generating SQL queries from natural language
- Classifying or tagging rows in a table
- Forecasting trends using built-in models
And yep, it’s all done through SQL. No need to spin up Jupyter notebooks unless you really want to.
Why This Matters
Snowflake Cortex isn’t trying to replace data scientists — it’s just making it way easier for anyone (even folks who aren’t coders) to tap into the power of AI. Whether you’re a data analyst, a product manager, or just AI-curious, you can now do more, faster — and without leaving Snowflake.
Final Thoughts
Snowflake Cortex is still pretty new, but it’s definitely one to watch. It brings the cool-factor of AI directly into the data stack without making your life harder.
Give it a spin, and maybe generate a few more haikus while you’re at it.