#1. Pilot
Topics: analytics, culture, late arriving data, MLOps, monitoring, visualization.
Uber’s Journey Toward Better Data Culture From First Principles — Uber Engineering Blog.
A lot of applicable ideas on how processes around data at scale can look like, areas of responsibility, and metrics of quality.
Visualizing Data Timeliness at Airbnb — Airbnb Engineering & Data Science @ Medium.
You should open this article only to view a perfect UI and feel a professional approach to building tools. Also, you can learn how to segregate different areas. We hope Airbnb will open this perfect tool in the near future.
Handling Late Arriving Dimensions Using a Reconciliation Pattern — Databricks Blog.
Several approaches to handle late-arriving dimensions. Problem statement and evolution of different approaches. Not so deep as you may expect but the core ideas are understandable.
Two steps towards a modern data platform — BigData Republic Blog.
One of the views on the organization of data teams. Transformation from centralized team to data mesh.
MLOps best practices — Towards Data Science @ Medium.
A quite extensive description of common pitfalls, which ML engineer may observe in process of ML products delivery in conjunction with best practices description.
