Open source BI adoption in 2026 is driven less by cost savings and more by the need for data ownership, deployment control, and the flexibility to integrate AI workflows without vendor dependency.

Over the past few years, database and analytics vendors have hopped on a bandwagon that may take us all to a destination where common data queries are free from the constraints of the specialist query ...

Abstract: Complex Text-to-SQL generation remains challenging due to the lack of explicit modeling of hierarchical schema structures and persistent semantic mismatches between natural-language queries ...

Abstract: Recent progress in Large Language Models has pushed Text-to-SQL systems closer to enabling natural language queries over complex relational databases. Unfortunately, the models sometimes ...

With the ecosystem of agentic tools and frameworks exploding in size, navigating the many options for building AI systems is becoming increasingly difficult, leaving developers confused and paralyzed ...

This is the official repository for the paper "E-SQL: Direct Schema Linking via Question Enrichment in Text-to-SQL". Translating natural language queries into SQL (Text-to-SQL) is a critical task for ...

Why is the language developers and DBAs use to organize data such a mess? Here are 13 reasons we wish we could quit SQL, even though we probably won't. For all its popularity and success, SQL is a ...

These books cover everything from beginner SQL queries to advanced database architecture. Perfect for developers, data analysts, and backend engineers. Learn performance tuning, indexing, ...

Even after 50 years, Structured Query Language, or SQL, remains the native tongue for those who speak data. It’s had impressive staying power since it was first coined the Structured Query English ...

1 Faculty of Science, Ontario Tech University, Oshawa, Canada. 2 Faculty of Business and IT, Ontario Tech University, Oshawa, Canada. 3 Legion Development Group, Oshawa, Canada. This study presents a ...