This demo showcases Cloudera Data Engineering's External IDE Connectivity, powered by the Spark Connect API. Data engineers can connect local IDEs like VS Code or Jupyter Lab to cloud clusters, run Spark workflows remotely, and sync code with GitHub. This feature enhances data engineering flexibility and productivity by streamlining CI/CD pipelines and enabling seamless synchronization between local and cloud environments, empowering downstream multi-functional analytics and AI.

AI promises efficiency, but are we implementing it the right way? @Marcus Merrell shares what’s critical to track AI usage and its impact: “Here’s the prompt I used to get this tool, and here are the changes I made to make it work.” This kind of transparency is non-negotiable. Start small with a group of mixed experience levels to uncover both benefits and risks before scaling. If AI adds overhead without solving core issues, is it truly worth the investment?

Logs have the power to preserve relationships between metrics, giving you deeper insights and a clearer picture of what’s happening in your system. Want to move from Observability 1.0 to 2.0? Start by making your logs work smarter. Watch the full QA Therapy episode to learn more!

In this webinar, industry expert will explore the latest trends in analytics, the growing impact of AI/ML, and the role of hybrid data infrastructures in modern data management. We’ll discuss the challenges of balancing legacy systems with modern cloud solutions and provide actionable insights to help organizations future-proof their data strategies. Whether you're looking to streamline data operations, enhance analytics capabilities, or align your data investments with business goals, this session will equip you with the knowledge to stay ahead in an ever-changing data ecosystem.