Day 1 | Hall 3 - Closed Door Workshops

Your pipelines work — until they don’t. And when they break at 2 AM, nobody knows why.

This workshop fixes that. You’ll learn how to bring real engineering discipline to data — CI/CD, automated testing, version control, and observability applied to pipelines the way software teams have done it for years.

We’ll get hands-on with orchestration frameworks like Airflow and Dagster, build data quality checks that catch issues before your stakeholders do, and implement lineage tracking so you always know what went wrong and where.

We’ll also connect the dots to LLMOps and ML pipelines, because reliable AI starts with reliable data. Bring your Python or SQL chops. Leave with pipelines that don’t page you at midnight.

Your warehouse got you this far. Your lake promised flexibility. But the future lives in between — the lakehouse.

This workshop tears apart the modern data stack and rebuilds it. You’ll go deep on Delta Lake, Apache Iceberg, ACID transactions, and schema evolution at scale. You’ll discover why semantic layers are quietly becoming the most important piece of the puzzle — turning data chaos into self-service analytics teams actually trust.

And because no data platform in 2026 is complete without AI, we’ll design architectures where feature stores, ML pipelines, and analytics don’t just coexist — they reinforce each other. Bring your SQL skills and curiosity. Leave with a blueprint you can use on Monday.