The three badges cover different parts of the Snowflake Cortex ecosystem — from getting started with Cortex Code, to exploring RAG, Text-to-SQL and CoCo, and finally understanding how to build intelligent data applications.
Getting Started with Cortex Code
Cortex Code introduces an AI-assisted development experience for working with Snowflake. The focus is on using natural-language interaction and AI assistance as part of the development workflow.
What I found interesting is the idea of bringing AI assistance closer to the actual data-development environment. Instead of treating an AI assistant as a completely separate tool, it can become part of the workflow used to explore, understand and work with Snowflake workloads.
- AI-assisted development for Snowflake workloads
- Natural-language interaction for development tasks
- Using Snowflake-aware AI assistance within the development workflow
Accelerate AI Development: Building AI Applications with Snowflake Cortex — RAG, Text-to-SQL & CoCo
This badge brings together three concepts that are becoming increasingly relevant when building AI applications around enterprise data: Retrieval-Augmented Generation (RAG), Text-to-SQL, and CoCo.
RAG
RAG combines retrieval with generation. Relevant information is retrieved from a data source and provided as context to an LLM, helping ground the generated response in the available information.
Text-to-SQL
Text-to-SQL allows users to ask questions about structured data using natural language. The question can then be translated into SQL, creating a more conversational way to interact with data.
CoCo
CoCo provides AI assistance for data and application development, helping developers work with SQL and Python through natural-language interaction.
- How RAG can ground LLM responses using retrieved context
- How natural-language questions can be translated into SQL
- How AI assistance can accelerate parts of Snowflake development
- How these capabilities can contribute to data-focused AI applications
Building Intelligent Data Applications with Snowflake Cortex
The third badge focuses on the broader idea of building intelligent applications around data using Snowflake Cortex.
From a data engineering perspective, this is an interesting shift. Traditional data platforms often focus on making data available for reporting, analytics and downstream processing. Intelligent data applications add another layer — enabling applications to use AI capabilities to interact with, search, understand and work with data.
The badge helped connect the individual AI capabilities with the bigger picture of building applications where data, AI and application logic work together.
- How AI capabilities can be brought closer to enterprise data
- How structured and unstructured data can support intelligent experiences
- The role of search, natural-language analytics and AI services in data applications
- How data engineering and AI application development are increasingly converging
Continuing to explore how AI can be combined with modern data engineering.