Building a Spark-Powered Platform for ML Data Needs at Snap

The Machine Learning (ML) community is pushing the boundaries of innovation, but this rapid advancement brings unique and significant challenges for data platforms. Standard solutions often fall short, leaving ML practitioners grappling with infrastructure complexities instead of focusing on their core models and insights. This post explores these challenges, why Apache Spark remains a cornerstone for scalable data processing, and how we're building a curated platform "Prism," to empower our ML teams.