Christophe Blefari

JANUARY 7, 2023

This year I deeply learned Superset—adding the tools to my tools expertise list. The blog crossed the 2000 members mark (❤️) and I won the best data science newsletter award. The year was so different to what I was expected. Maybe this is an excuse. Anyway I did not reach my goals. Happy reading.

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ProjectPro

FEBRUARY 21, 2023

This blog will explore the need for image-processing and various python image processing libraries available to computer vision engineers for different use cases. stars and more than 994k users on GitHub indicates how popular it is among data science enthusiasts. Isn’t that interesting? The fact that it has over 10.5k

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Maxime Beauchemin

JANUARY 20, 2017

In relation to previously existing roles , the data engineering field could be thought of as a superset of business intelligence and data warehousing that brings more elements from software engineering. I joined Facebook in 2011 as a business intelligence engineer. By the time I left in 2013, I was a data engineer. We were pioneers.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

Pinterest Engineering

JANUARY 18, 2024

In this blog, we will focus on some online and offline discrepancies and development cycle learnings we have observed in Pinterest ads conversion models, as well as some of the key platform investments Pinterest has made to minimize such discrepancies. People often come to Pinterest when they are considering what to do or buy next.

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Data Engineering Weekly

DECEMBER 11, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Sign up free to test out the tool today. Should I write another prediction? What I’m planning to write?

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Maxime Beauchemin

FEBRUARY 28, 2017

In The Rise of the Data Engineer , Maxime defined data engineering as: The data engineering field could be thought of as a superset of business intelligence and data warehousing that brings more elements from software engineering. The data engineering toolbox is how we make sense of it all quickly and at scale. We should expect 1.8.0

Data Engineering 130

Data Engineering Data Engineer Engineering Data Pipeline 130

Airbnb Tech

APRIL 13, 2021

The path to cloud efficiency begins with a cost data foundation by Anna Matlin and Tamar Eterman Introduction Business profitability and sustainability are powerful reasons to invest in infrastructure efficiency, but it is easy to feel lost about how to actually reduce costs. Most teams at Airbnb rely on the data warehouse (i.e.,

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