Self-Service Data Prep: a Gartner Guide

Neoclouds offer performance specialization, which increasingly is factored into what some call multi-compute strategies. In general, what that means is that enterprises are using hyperscalers for general workloads, neoclouds for model training, and edge infrastructure for inference.

To implement a successful agentic AI initiative, business leaders need to define clear jobs with measurable impact, ensure tight cost controls, and construct strong guardrails around these systems.

Quantum disruption is coming. Readiness built through knowledge, crypto-agility, and thoughtful prioritization will create organizational resilience now without forcing exorbitant investments later.

The IBM acquisition of Confluent is indicative of the tech world’s fixation on real-time data streaming. However, the more pressing issue is the overwhelming volume of unstructured documents that hold the critical context that real-time AI often overlooks.

Boring AI earns trust because it works. It removes friction from daily tasks, and over time, that trust becomes the foundation for more ambitious systems.

In this week’s real-time analytics news: IBM launched Db2 Genius Hub, which brings autonomous capabilities to Db2.

Neoclouds offer performance specialization, which increasingly is factored into what some call multi-compute strategies. In general, what that means is that enterprises are using hyperscalers for general workloads, neoclouds for model training, and edge infrastructure for inference.

What ultimately differentiates high-performing manufacturers isn’t just the tools they use, but the mindset they cultivate. Leaders in these organizations emphasize proactive decision-making, accountability, and continuous improvement.