Systems | Development | Analytics | API | Testing

Brittle pipelines and SLA firefighting hold data teams back. Agentic data engineering introduces autonomous AI agents that detect failures, fix code, and re-run pipelines—with humans in the loop guide critical decisions. This video explains how Cloudera Data Engineering and Cloudera AI enable self-healing pipelines.

AI may be the most capable intern your organization has ever hired. However, interns still need guidance and clear direction. Enterprise AI is proving no different. In this episode of The AI Forecast, Paul Muller sits down with Michael Gray, CTO of Thrive, to explore the patterns and anti-patterns emerging from real-world enterprise AI deployments. Drawing on his experience helping organizations implement AI at scale, Michael offers a practical framework for evaluating AI maturity, helping leaders understand where adoption breaks down and what it takes to build momentum across the organization.

Struggling to get clear, reproducible insights from petabytes of data? Join Charu Anchlia, Principal Engineer II at Cloudera, to see how Cloudera Agent Studio brings business users and tech analysts together under one simple interface. See how multi-agent orchestration—using specialized SQL and coding agents—can solve complex data analysis challenges, generate real-time visualizations, and seamlessly transform LLM outputs into repeatable Airflow pipelines.

The fastest way to AI might not be adding more tools. It might be getting more value from the data you already have. Discover how Cloudera optimizes your cloud infrastructure costs without disrupting your running business applications. This framework drastically lowers your data preparation and data readiness overhead while giving your teams total flexibility to use the analytics tools of their choice.

For decades, network teams have been forced to choose between speed and stability. AI may finally be changing that equation. In this episode of The AI Forecast, Paul Muller sits down with John Capobianco, Head of AI and Developer Relations at Itential and author of “Automate Your Network,” to explore how AI is reshaping the future of network operations. Drawing on decades of experience in network engineering, John explains why network automation has struggled to gain traction and how AI, agents, and Model Context Protocol (MCP) could finally break the bottleneck.

The AI worker shakeup is here, and the scale is monumental. While tech giants chase grand singular visions, real employees are facing a massive displacement crisis that traditional tribunals and narrow regulations aren't equipped to handle. Are we moving too fast to protect our workforce?

Meetup Date - 30th May 2026 10:30AM to 2PM Where - Cloudera Bangalore Office Subscribe to stay ahead of the curve with the latest in data strategy, open architectures, and enterprise AI innovations.

AI governance is already struggling to keep pace. Add quantum computing and space infrastructure, and the challenge becomes exponentially harder. In this episode of The AI Forecast, Paul Muller sits down with technology governance specialist and researcher Preetha Bedi to explore the growing convergence between AI, space, and quantum technologies—and why this nexus is creating entirely new categories of systemic risk.

Ever wonder why so many enterprise AI projects never make it past the pilot stage? It’s not the AI—it’s the foundation. In this video, we break down why rushing into complex models without fixing inconsistent data, fragile pipelines, and afterthought governance is a recipe for failure. Fix the basics first!

Are you actually building an open data platform, or are you just using open source file formats inside a new type of vendor lock-in? Many organizations assume that migrating to Apache Iceberg or Parquet automatically makes their data architecture open. However, true architectural freedom requires a strategy that spans across your entire data estate—not just the storage layer.