Data management has traditionally forced organizations into an uncomfortable choice: use data warehouses for structured analytics or data lakes for flexible, large-scale storage. For years, this meant maintaining separate systems, duplicating data, and dealing with the headaches that come with disconnected infrastructure. The data lakehouse emerged as an answer to this problem, offering a unified approach that gives you the best of both worlds.

Agentic AI is transforming how we think about artificial intelligence, representing a shift from passive tools that wait for instructions to proactive systems that can think, plan, and act independently to achieve goals.

AI observability provides deep visibility into AI systems beyond traditional monitoring, tracking data quality, model performance, infrastructure, and ethical compliance. It's essential for detecting silent model degradation, managing complexity at scale, and building trust in AI systems. Organizations implementing AI observability gain faster troubleshooting, optimized performance, and better risk management.