Systems | Development | Analytics | API | Testing

The New Requirements for Mission-Critical Storage in an AI-Driven Enterprise

Most enterprises have made the commitment to AI. They’ve approved the budgets, stood up the pilots, and named it a strategic priority. So why are 95% of them getting zero return on $30–40 billion in GenAI investment? According to MIT research cited in Hitachi Vantara’s 2025 State of Data Infrastructure Global Report — which surveyed more than 1,200 IT leaders across 15 markets — the failure isn’t the model. It’s the infrastructure underneath it.

What CTOs Need to Know About Modern AI Storage

As organizations scale their AI initiatives from experimentation into production, CTOs face a pivotal architectural challenge as storage emerges as one of the most common—and most expensive—constraints. While organizations continue to invest aggressively in GPU compute, studies consistently show that infrastructure inefficiencies outside the GPU account for the majority of wasted AI spend.

Ep 65 | The Vibecoding Liability: How Unchecked AI Can Kill Cloud ROI

Cloud computing promised efficiency, scalability, and reliability. But as AI workloads grow more complex, many enterprises are learning the hard way that these promises don’t come automatically. In this episode of The AI Forecast, Paul Muller sits down with Linthicum Research founder David Linthicum to talk through the real state of hybrid cloud strategy and enterprise architecture in the age of cloud computing and AI.

Real-Time Streaming Data & Insights with Cloudera Data in Motion #Cloudera #AI #Tech #Shorts

Discover how Cloudera Data in Motion captures, processes, and delivers streaming data the moment it is created. Using DataFlow and over 450 connectors, you can enrich data in flight to gain instant insights securely and at scale. Learn how a global financial institution successfully cut costs and improved fraud detection by replacing traditional batch workflows with real-time streams. Ensure your business never stands still by keeping your data always in motion.

Launching Project SnowWork - Bringing Outcome Driven AI to Every Business User

Project SnowWork empowers business teams to automate multi-step workflows end-to-end, and drive real outcomes. Create revenue snapshots, diagnose missed forecasts, and generate summary slides with next steps — all without any coding experience needed.

The End of Busywork: Meet Project SnowWork

Introducing Project SnowWork. An autonomous AI platform that embeds intelligence directly into your business workflows and tools. Project SnowWork brings Snowflake's vision for the agentic enterprise to life, where enterprise data, intelligence, and action are connected in a governed way. Launching in research preview to a limited set of customers, Project SnowWork handles complex, multi-step tasks and delivers real, data-driven outcomes to business users.

Cloudera Agent Studio and NVIDIA Bring Next-Gen Agents to Enterprise AI

Autonomous agents act toward complex goals without requiring human direction at each step. In enterprise environments, deploying these agents introduces a more exacting set of challenges: they must navigate heterogeneous data systems; satisfy compliance, audit, and data sovereignty mandates; and keep all data within the organization's operational boundary.

Legacy VM Footprints are Holding Back Digital Transformation

Enterprises in 2026 are under increasing pressure to modernize applications, adopt hybrid cloud architectures, and streamline operations—but their expanding and aging VMware footprints have become a major obstacle. As VMware licensing models evolve and operational costs climb, reducing or restructuring this footprint has become just as critical as adopting new platforms.