Event streams are central to delivering actionable insights for analytics and AI. However, without rich metadata to contextualize these streams, data consumers often struggle with inconsistencies, poor quality, and a lack of interpretability. By leveraging metadata as a cornerstone of event stream architecture, organizations can unlock clarity in their streaming data, bridging the gap between raw event streams and actionable insights. This clarity not only enhances the quality and usability of event streams but also ensures alignment between developers, analysts, and AI systems, enabling them to extract maximum value from data in motion.

This session explores how rich metadata transforms event streams into a reliable foundation for advanced analytics and AI workflows. We will examine the role of schema definitions, semantic annotations, and cataloging practices in improving data quality and context. Attendees will gain practical insights into building metadata-enriched event stream pipelines, fostering collaboration between data producers and consumers, and enabling AI models to operate with greater precision. Whether you are developing real-time applications or enhancing decision-making with AI, this talk will provide actionable strategies to harness the power of rich metadata in event streaming.