Every data engineering team right now is being asked the same question: "How do we build a chatbot that talks to our data?" The prototypes are deceptively simple. A developer connects GPT-5.1 to a ...

Abstract: Current Text-to-SQL methods are evaluated and only focused on executable queries overlooking the semantic alignment challenge both in terms of the semantic meaning of the query and the ...

In most enterprises, data access still feels like a locked room with SQL as the only key. Business teams depend on data engineers for every report, dashboard, or metric tweak. Even in the age of ...

Abstract: Aiming to reduce the learning cost of database operations, Text-to-SQL methods provide a strategy of automatically generating structured query language (SQL), which is an active research ...

Semantic SEO helps search engines understand context. Learn how to use entities, topics, and intent to build richer content that ranks higher. Semantic SEO aims to describe the relationships between ...

Workflow is still at the heart of the new framework. Building on the strengths of the Semantic Kernel and AutoGen agent implementations, the new framework offers support for workflow orchestration and ...

Discover how Tinker and Ray are utilized to fine-tune text-to-SQL models, enhancing AI capabilities in generating efficient SQL queries. In an innovative approach to advancing text-to-SQL models, ...

When using the Semantic Kernel SDK with the Group Chat Orchestration pattern, we observe a token usage discrepancy between the SDK’s reported values and those shown in the Azure portal. Create an ...

In this tutorial, we build an advanced AI agent using Semantic Kernel combined with Google’s Gemini free model, and we run it seamlessly on Google Colab. We start by wiring Semantic Kernel plugins as ...

While data warehouses and cloud-native architectures have grown rapidly, business users are still finding it difficult to reach enterprise data. Even as dashboards and query tools become easier to use ...

A new SQL Server 2025 feature lets organizations run vector-based semantic searches on their own data, connecting to local or cloud-hosted AI models without relying on massive general-purpose LLMs. I ...