☀️ Happy Friday. This week we have six new articles about data engineering but not only! From Back Market learning on Delta Lake to Reddit rex on recommendation.

Back Market — Subscriptions on a Delta Lake

Back Market engineering explains how they used Delta Lake to get data from production and then push it to Snowflake or S3.

Subscriptions on a Delta Lake

After moving data out of our Monolith’s database and preparing it to be consumed for multiple usages by our business stakeholders, the manifesto of our Data Engineering teams includes that we have to…

Back Market EngineeringFlorian Valeye

Do we need new editor for SQL analysts?

Robert Yi asserts that IDE are not the future of SQL analytics and propose a solution with his new company to fix this. He started prequel.ai in order to help closing the gap.

Why the IDE is not the future of SQL-based analytics

I’m just going to say it: the traditional IDE format is not great for writing queries for analytics work. I’ll start by explaining why, then tell you what you can do about it. First, my explanation —…

Towards Data ScienceRobert Yi

Fivetran for collection in the Modern Data Stack

We all read the Modern Data Stack article from dbt CEO Tristan Handy (if not, go now!). Here Fivetran tries to write a small summary about this matter.

What Is the Modern Data Stack? | Blog | Fivetran

A radically new approach to data integration saves engineering time, allowing engineers and analysts to pursue higher-value activities.

Fivetran

State of reverse ETL

A nice articles filled with charts on with market share of reverse ETL tools. We see that Snowflake and BigQuery have trully taken the lead in integrations regarding source, and for destination at least 40% of the tools are used for CRM.

The State of Reverse ETL: What Operational Analytics Will Look Like in 2021 and Beyond

A deep-dive into how companies are using Reverse ETL in 2021 to power their operational workflows

Hightouch

Tips and tricks to setup your PostgreSQL as a DWH

Imagine a world where Snowflake and BigQuery does not exist. In this world you will need to configure your Postgres to act like a data warehouse, this article deep dives in the Postgres configuration to tune this perfectly. I like the Partitioning tip!

Using PostgreSQL as a Data Warehouse

With some tweaking Postgres can be a great data warehouse. Here's how to configure it.

Narrator Data Blog | Narrator.aiCedric Dussud

ML Friday, the Reddit journey on recommendation

Reddit shared their journey on from no recommendation to 100 billion recommendations a day. They speak about feature store and model feedback loop to improve predictions. A must read!