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 ...

Capturing tribal knowledge organically and creating a living metadata store that informs every AI interaction with ...

Data work in 2026 asks for more than chart building. Professionals are expected to clean data, query databases, explain trends, and present findings clearly across business, finance, product, and ...

SQL Server backups cannot be restored to older versions directly. Use Export and Import Data-Tier Application for cross-version database migration. Reconfigure permissions, logins, and connection ...

Atelier Intégration des Données - Big Data ETL avec Apache Spark ...

I am a Backend Developer and Software Engineer with a solid background in Artificial Intelligence in academic and professional fields, looking forwa ...

Design and implement an end-to-end ETL (Extract, Transform, Load) pipeline using SQL for data extraction and transformation, and Python for orchestration and automation. Use any open dataset (e.g., ...

Millions of users work with SQL to keep the gears of their business turning. In an era marked by relentless digital transformation, the proliferation of AI workloads, and tightening regulatory demands ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Abstract: Generating accurate SQL from users’ natural language questions (text-to-SQL) remains a long-standing challenge due to the complexities involved in user question understanding, database ...