In collaboration with Data Engineers London

Intelligent Snowflake Warehouse Management Konrad’s session explores how Crisp automated Snowflake warehouse management to cut costs and boost efficiency. Using their open-source dbt package dbt-macro-polo, the team built a system that automatically selects the right warehouse size for each workload, adapts by environment, and removes manual scaling. The result: predictable performance, lower compute spend (up to 80% reduction), and a smoother developer experience across teams—all achieved through intelligent automation directly in dbt. From Stadiums to Scaled Data: Lessons in Real-Time Data at Global Scale Sam’s session dives into lessons from large-scale live event data systems—handling over 10 billion data points per second for global tours like Beyoncé, Coldplay, and Glastonbury. He connects the extreme demands of real-time analytics and high-performance networking to modern cloud data practices, showing how the same principles of speed, resilience, and precision apply when designing reliable, scalable data platforms today.