Mission Data Possible - Rethinking Data Architecture

Explore a comprehensive conference talk that challenges conventional approaches to data architecture in modern machine learning environments. Learn how to fundamentally rethink data infrastructure design principles to better support ML operations and production workflows. Discover innovative strategies for organizing, managing, and scaling data systems that can handle the complex requirements of machine learning pipelines. Examine real-world case studies and practical examples that demonstrate how reimagined data architectures can improve performance, reliability, and maintainability in MLOps environments. Gain insights into emerging patterns and best practices for building data foundations that truly enable successful machine learning in production, moving beyond traditional data warehouse and lake concepts to more flexible and ML-optimized approaches.