Learn how to detect and scope an adversary who signs in to Databricks with a credential, using system tables, audit logs, and ...

Many companies are working on connecting AI agents to their internal data warehouses (such as Snowflake or BigQuery) to allow ...

Amazon Web Services has detailed a serverless MCP architecture that allows multiple AI agents to access enterprise data lakes ...

This article is the Japanese version of a post published on STEALIEN's Korean technical blog in December 2022. It introduces ...

Your model will keep getting better at writing SQL. To make it trustworthy, nail down the access rules before tuning for ...

This application allows users to convert natural language queries into SQL queries. It leverages advanced natural language processing (NLP) and machine learning techniques to understand and translate ...

Medallion pipeline over 128M CMS Part D prescriber-drug rows with GLP-1 marts, and a text to SQL agent scored on a hand-written golden set with MLflow - AbhayJuloori/glp1-partd-lakehouse-text2sql ...

There is no tool for browsing raw schemas. NVIDIA chose that on purpose, so agents reach data through the semantic layer. The ...

An enterprise agent can fail or run up an unbudgeted bill before the language model writes a word. Berlin startup SereneDB is betting that fusing search and analytics can tame both the evidence ...

Overview: Google Cloud's Agentspace helps businesses build AI agents that search company data, plan tasks, and automate workflows.Companies like Telus, Suzano, ...

Data warehouses are often subject to a preponderance of ad-hoc queries. They came into existence in the 1990s to support historical data stores of customer-facing data, especially sales data. At that ...