Surviving the data journey: a case study of migrating ML-engine.

In this presentation I will delve into the challenges of Machine Learning (ML) engine migration from a data engineering perspective. Given a migration is a typical undertaking for outsourcing companies like Globallogic, I will show how lack of proper data management and utilization could make this process a nightmare for developers as well as for customers. I'll focus on the importance of building resilient pipelines, clearly separating data engineering and ML tasks, and other data engineering best practices with examples.