Actian’s Ole Olesen-Bagneux explains why AI agents need metadata, lineage, context, and governance before enterprises can trust them at scale.

In today’s data-driven world, the ability to visualize and interpret complex datasets has become a crucial skill. Businesses, non-profits, and government agencies alike rely heavily on data to make ...

Spread the love“`html Understanding how to open a port in firewall is essential for anyone working with networks, whether it’s for personal use, gaming, or business applications. Firewalls serve as ...

The best Power BI courses in 2026 are essential for professionals aiming to master data-driven decision-making and business ...

Azure Functions shipped a serverless agents runtime in public preview at Build 2026. Agents are defined in .agent.md markdown ...

Effective prompts use four core elements. Start by assigning a role, then give background context, state a clear task with an ...

You really don’t need that many steps anymore.

A woman with advanced Alzheimer’s disease saw significant improvements in brain function after taking psilocybin-containing mushrooms. That’s according to a case report recently published in Frontiers ...

Stop manually updating Excel charts by mastering dynamic ranges, spill operators, and custom threshold lines for seamless ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the ...

Section 1. Purpose. The United States continues to lead the world in Artificial Intelligence (AI) because of the enormous talent and innovation of our AI industry, and because we refuse to stifle this ...