TL;DR AI risk doesn’t live in the model. It lives in the APIs behind it. Every AI interaction triggers a chain of API calls across your environment. Many of those APIs aren’t documented or tracked.

Introduction: Why Cloud Microsegmentation Must Evolve Cloud-native architectures built on auto-scaling virtual machines, platform-as-a-service (PaaS), and serverless platforms have transformed ...

Artificial intelligence has become embedded in nearly every operational layer of modern institutions. It parses documents, ...

Tech executives explain how they're moving beyond legacy Excel mapping to build AI data pipelines that cut integration ...

Open-source platform with 30+ MCP tools lets AI agents autonomously create pipelines, query databases, search vector ...

Oracle announced a suite of agentic AI capabilities integrated directly into Oracle AI Database, enabling AI agents to securely access enterprise data where it already exists, rather than requiring ...

This week, we are excited to kick off SQLCon 2026 alongside FabCon in Atlanta. Bringing these SQL and Fabric communities together creates a unique opportunity to learn, connect, and share what’s next ...

This infographic is part of a series that maps different EU digital laws with the GDPR. The full series can be accessed here. The EU Data Act creates new rules on who can access and use data generated ...

With agentic AI, the database must evolve from a passive ledger to an active reasoning engine that informs, guides, and enables autonomous action. For decades, the database has been the silent partner ...

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 ...

Data is the lifeblood of modern business. The value of any business decision starts and ends with data quality. This is why bad or incomplete databases can completely cripple a business, and why you ...