It's been a long week, please forgive me, I pick the most obvious picture (credits)

Hey there. This is it. I'm in now in Berlin so if you wanna meet, say hi, I have plenty of time to meet new people.

Here the weekly data news everyone's waiting 🙃.

Data fundraising 💰

When Forbes talks about tech

Last week Forbes released their Cloud 100 a list that ranks — according to them — the top 100 private cloud companies. In this ranking around 10 companies are really about data. This is the stuff we speak about every Friday. They also discussed about Databricks, Fivetran and dbt Labs valuations that skyrocketed recently and what is means for their future.

We all live in a CTE hell loop

Cloud warehouses really popularized Common Table Expressions because in the past CTEs were in disgrace. CTE offers flexibility and linear structure to a SQL query that helps us achieve wonderful thousands lines SQL.

If you want to understand what are CTEs this week Brian wrote a guide on how to approach CTEs when you come from the subselect world. As a side note I also discovered the recursive CTE. It looks like hell.

A recursive CTE (credits)

How to use dbt's run_results.json

This is a great post about how you can use the run_results.json artifact to create your own metrics dashboard to achieve dbt observability. I really like this topic because dbt artifacts are a really powerful way to own your dbt projects and to find incremental boost in performance.

Things I wish I knew...

ML Friday 🤖

Aren't the interactive websites the best ones when it comes to understand a machine learning model? Few weeks ago I shared Random Forest explained. This week the MLU-EXPLAIN did it again with the Logistic Regression. This is a cool web app where you discover stuff while you scroll on the page.

If you want to go further regarding machine learning you can still register to the free Machine Learning Zoomcamp created by Alexey. This is a 4 months program which looks really neat. To finish this category I propose you Vinija's notes about Stanford's NLP with Deep Learning course.

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Faster ML Experimentation at Etsy with interleaving — tbh this is not something I'm able to understand when I've written 700 words in the newsletter. But I hope ML Friday's readers will like it 🤓.

PS: Meta wrote a post about Scaling data ingestion for machine learning training. But they removed the post. If you still want to see the verbatim I managed to save it on this gist (sorry Meta). In a nutshell they reduced their data center power consumption by 35-45 percent.

This picture appeared when I type logistic regression (credits)

Fast News ⚡️