View profile

Analytics is a Mess. Good DS, Bad DS. Analytics Engineering vs. Data Engineering. Understanding the Optimizer. [DSR #252]

Analytics is a Mess. Good DS, Bad DS. Analytics Engineering vs. Data Engineering. Understanding the Optimizer. [DSR #252]
By Tristan Handy • Issue #252 • View online
❤️ Want to support this project? Forward this email to three friends!
🚀 Forwarded this from a friend? Sign up to the Data Science Roundup here.

This week's best data science articles
Rahul Jain
Data engineers love building complex Rube Goldberg machines which can be easily replaced with simpler systems that run at a fraction of the original cost.
This tweet is a very succinct summary of one of the most important posts that I’ve ever read: Engineers Shouldn’t Write ETL. If you find yourself saying, “hey, data engineers are valuable!” you’re not wrong–it’s that the org structure that they typically operate in leads to very poor outcomes and rampant mediocrity. Read the above post to understand why that’s the case. It’s just as true today as the day it was penned in 2016.
Mark Saroufim
Popular Dev Tools aren't just solving a problem. They solve core emotional needs
* HuggingFace makes you feel smart
* Unity makes you feel like a kid again
* Github makes you feel seen
* Fastai makes you feel like you belong
* VSCode makes you feel like a tinkerer
Most Common Professional Marriages
How does using dbt make you feel? Reply here.
Thanks to our sponsor!
dbt: Your Entire Analytics Engineering Workflow
Did you enjoy this issue?
Tristan Handy

The internet's most useful data science articles. Curated with ❤️ by Tristan Handy.

If you don't want these updates anymore, please unsubscribe here.
If you were forwarded this newsletter and you like it, you can subscribe here.
Powered by Revue
915 Spring Garden St., Suite 500, Philadelphia, PA 19123