Move Fast and Don't Break Things - How to Build a Scalable Data Platform

Explore the intricacies of building a scalable data platform in this 35-minute conference talk from Data Council. Dive into Machine Learning Operations as Elijah Ben Izzy, Co-founder & CTO of DAGWorks Inc., shares insights from his experience at Stitch Fix. Learn about the two-phase process of deploying ML models, focusing on the open-source library Hamilton. Gain valuable knowledge on overcoming challenges faced by large data science teams, discover practical solutions using Hamilton, and compare it with other industry tools. Understand strategic goals for platform development, explore concepts like cognitive dissonance in data workflows, and examine real-world applications in quantitative finance and machine learning pipelines. Delve into topics such as getting started with Hamilton, scaling operations, ensuring data quality, and customizing workflows. Acquire insights on production use cases, tokenization, summarization, and a new approach to data platform abstraction.