The purpose of the Text-to-SQL task is to bridge the gap between natural language and SQL queries. Current approaches mainly rely on large language models (LLMs), but employing them for Text-to-SQL ha ...

Everyone talks about AI risk at the model layer. Bias in training data. Hallucinations. Explainability. Model governance. Model monitoring. No one talks about the schema layer. And that’s exactly ...

In this tutorial, we build an advanced, end-to-end learning pipeline around Atomic-Agents by wiring together typed agent interfaces, structured prompting, and a compact retrieval layer that grounds ...

I am a Senior Member of Technical Staff at Salesforce, where I build AI-driven enterprise solutions that integrate LLM. I am a Senior Member of Technical Staff at Salesforce, where I build AI-driven ...

Existem várias ferramentas de IA e assistentes inteligentes que ajudam a criar diagramas de esquemas (schemas) para planejamento de sistemas, como bancos de dados, arquitetura de software e fluxos de ...

Abstract: This paper introduces G-SQL, a schema-aware and rule-guided framework for translating Natural Language Queries (NLQ) into SQL, designed to support users with limited technical expertise.

Microsoft is making it easier to migrate to Azure SQL by taking the grunt work out of schema setup. A new update to Azure Database Migration Service (DMS) introduces a built-in schema migration tool ...

Why do some public policies mandated by the highest levels of government succeed, while others fail? This essay offers a partial answer by proposing that the effectiveness of a public policy depends ...

Hello there! 👋 I'm Luca, a BI Developer with a passion for all things data, Proficient in Python, SQL and Power BI ...

This tutorial will guide you through the process of using SQL databases with Python, focusing on MySQL as the database management system. You will learn how to set up your environment, connect to a ...