MetaOps - Metadata Operations for End-to-End Data and Machine Learning Platforms

Explore the challenges and solutions in metadata management for large-scale data and machine learning platforms in this 37-minute conference talk by Alejandro Saucedo from The Institute for Ethical AI & Machine Learning. Dive into the complexities of integrating multiple frameworks across the machine learning lifecycle, and learn about the growing importance of metadata collection, tracking, and management. Discover tooling, best practices, and solutions to address interoperability bottlenecks, ensure compliance, and maintain lineage, auditability, accountability, and reproducibility. Gain insights into the rise of metadata management systems, their successes, and critical shortcomings that require ecosystem-wide collaboration for long-term robustness in heterogeneous end-to-end platforms.