Natural language-based database analytics with Amazon Nova

In this post, we explore how natural language database analytics can revolutionize the way organizations interact with their structured data through the power of large language model (LLM) agents. Natural language interfaces to databases have long been a goal in data management. Agents enhance database analytics by breaking down complex queries into explicit, verifiable reasoning steps and enabling self-correction through validation loops that can catch errors, analyze failures, and refine queries until they accurately match user intent and schema requirements. We demonstrate how this modern approach enables intuitive, conversation-like interactions with complex database systems while maintaining precision and reliability.

To achieve optimal performance with minimal trade-offs, we use the Amazon Nova family of foundation models (FMs): Amazon Nova Pro, Amazon Nova Lite, and Amazon Nova Micro. These FMs encode vast amounts of world knowledge, facilitating nuanced reasoning and contextual understanding essential for complex data analysis. Our solution uses the ReAct ...