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.

Enterprise AI Infrastructure Security - 4) Service Accounts & Automation Security

Securing ClearML for the Enterprise — Part 4: Service Accounts & Automation Security In this video we walk through ClearML's service accounts — the identities behind your automated workloads — and how impersonation ensures least-privilege execution across your agents, pipelines, and schedulers.

Enterprise AI Infrastructure Security Series - 5) Compute & Data Access Governance

Securing ClearML for the Enterprise — Part 5: Compute & Data Access Governance In this video we walk through ClearML's compute governance layer — resource pools, resource profiles, and resource policies — and how they work together to give every team fair, governed access to your GPU infrastructure while keeping it fully utilized. What we cover: Previous videos in this series.

How CARIAD Powers Software-Defined Vehicles with Real-Time Data Streaming | Life Is But A Stream

45 million vehicles, 90 markets, 12+ iconic brands, each with its own data silos, standards, and infrastructures. In this episode, Chetan Alatagi, Solution Architect reveals how they transitioned from fragmented legacy ETL silos to a Unified Data Ecosystem—a global data streaming highway that turns vehicle telemetry into real-time value.

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.

Your AI agent is one misconfigured MCP server away from leaking production data.

2025 was vibe coding. 2026 is Agentic Engineering - and the security rules haven't caught up. AI agents now have direct access to your databases, your APIs, your Kafka clusters. The protocol giving them that access is MCP. And most teams have no idea how exposed they are. We are fixing this problem with OAuth 2.1.

Lenses 6.2 - Trusting Agents to build & operate event-driven applications

At Lenses, our goal has always been to help organizations get the most out of their streaming data. We started with visibility into the Apache Kafka, moving up to the part that drives value, the application layer and now the Agentic layer. Lenses 6 moved us into a multi-Kafka world, as increasing, our clients aren’t just running on one type of Kafka anymore, and as sovereign cloud becomes increasingly topical (no pun intended) this is only increasing.