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How to learn data engineering

Christophe Blefari

Learn data engineering, all the references ( credits ) This is a special edition of the Data News. But right now I'm in holidays finishing a hiking week in Corsica 🥾 So I wrote this special edition about: how to learn data engineering in 2024. The idea is to create a living reference about Data Engineering.

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Data Engineering in Retrospect: Key Trends and Patterns of 2023

Data Engineering Weekly

It’s the end of the year, and there will be a lot of buzz about what the next five years in data engineering might bring. source: Meta - The future of the data engineer Companies are at various stages of this model, which means certain patterns and predictions may align with your organization's maturity level while others might not.

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GPT-based data engineering accelerators

RandomTrees

GPT-based data engineering accelerators make the working of data more accessible. Overall, GPT-based data engineering accelerators are very efficient and beneficial for organizations. GPT-Based Data Engineering Accelerators: Given below is the list of some of the GPT-based data engineering accelerators. 1.

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#ClouderaLife Spotlight: Amogh Desai, Software Engineer II

Cloudera

This month’s #ClouderaLife Spotlight features software engineer Amogh Desai. Snatching victory from the jaws of defeat Amogh and his fellow hackathon team members felt the rush of victory after winning Cloudera’s 2022 global hackathon in the product development category. One way he does this is through blog writing.

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Data Engineering Weekly #124

Data Engineering Weekly

Data Engineering Weekly readers get a 20% discount by applying Promo Code: DataWeekly20 Data Council website: [link] The Real-Time Analytic Summit is on April 25-26 in downtown San Francisco, CA. dbt: State of Analytics Engineering dbt publishes the state of analytical [data???🤔] 🤔] engineering.

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An Engineering Guide to Data Quality - A Data Contract Perspective - Part 2

Data Engineering Weekly

I won’t bore you with the importance of data quality in the blog. The industry follows two categories of data processing techniques to handle the trade-off between speed and correctness. In the second part, we will focus on architectural patterns to implement data quality from a data contract perspective. How to Fix It?

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Data Engineering Weekly #109

Data Engineering Weekly

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. I have a long list of thoughts on this conversation, which might need a blog post on its own.