#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.

level:beginner topic:culture


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.

level:medium topic:visualization topic:monitoring


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.

level:advanced topic:late-arriving-data


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.

level:beginner topic:analytics


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.

level:medium topic:mlops

Written on April 21, 2021