Unlocking Your Business Data: How New AI Tools Talk to Your Databases

AI discusses how Large Language Models (LLMs) can effectively interact with structured business data, such as databases, overcoming initial skepticism that these language-centric AIs couldn't handle numerical information. It introduces the Model Content Protocol (MCP) as a crucial standard acting like a universal translator, enabling LLMs to connect with various data sources. The document explains how LLMs translate natural language questions into database queries and back, leveraging a "human-augmented database description" to navigate messy real-world data and infer complex relationships between tables. Furthermore, it highlights the power of Query Log Mining, where LLMs learn from a company's historical data interactions, including successful and failed queries, and even assist in identifying and managing "garbage" or obsolete data within databases, transforming data governance into a more dynamic, AI-assisted process.