#33. Thoughts on privacy and privacy of thoughts
Topics: Architecture, databases, data mesh, data privacy, data thoughts, storage engine
Dynamic Filtering: a Critical Performance Optimization in Analytical Engines — Vladimir Ozerov @ Querify Labs Blog
Let’s continue getting acquainted with the query engine optimization techniques with developers of these query engines. Now it’s dynamic filtering time.
Data Mesh in practice: Product thinking and development (Part III) — Ammara Gafoor, Ian Murdoch, Kiran Prakash @ Thoughtworks Blog
There are 4 articles in this series, but I want to share this one with you because Data Product itself is closer to data engineers (from my point of view). But we’re often not aware of what it truly is and how is it built. So let’s fill the gap.
Other articles in the series: Part I, Part II, Part IV.
Privacy Enhancing Technologies: An Introduction for Technologists — Katharine Jarmul
A new article about Privacy Enhancing Technologies (PETs) in Martin Fowler’s blog. In the era of systems like ChatGPT or Stable Diffusion personal data privacy is especially important. This article is a great intro to PETs and provides some use cases on how to protect your data in the modern world.
The State of Data Engineering 2023 — Einat Orr @ lakeFS blog
It’s time to reveal new State of Data Engineering with lakeFS!
Why Uber Engineering Switched from Postgres to MySQL — Uber Engineering Blog
Uber started with a monolithic backend application that used Postgres. As the company evolved and grew, it moved to microservices and changed its approach to working with data. The paper explains why this migration happened and what benefits the company gets from it. There is nothing about OLAP in the paper but still a very interesting story.
