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🐰 #30 Downfall of the Data Engineer, Open Data Collaboration, Building Mega Open-Source Projects; ThDPTh #30 🐰
The downfall of the data engineer, why open data collaboration has problems, and how to build the next mega open source project.
We’ve made it to 30! Yay! I obviously like to write, so I’m going to continue, whether there are a hundred people receiving this or a thousand, but it is more fun if people read it and give feedback so, I got two asks for you:
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Let’s dive into it….
Data will power every piece of our existence in the near future. I collect “Data Points” to help understand & shape this future.
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🎁 (1) Open Data Collaboration, Runeson
Prof. Runeson took up the topic of open data collaboration in a paper from 2020. Open Data Collaboration is simply the idea of sharing data just like code in some kind of “GitHub”-like worldwide project. Or at least that’s the version I would have in mind, as decentralized local efforts seem very detrimental to such projects because of the necessary network effects needed to make such things work.
I’m sharing this paper mostly because I like that people start exploring this topic. The findings itself in the paper to me seem that:
1) It’s pretty important to get open data collaboration going sometime soon,
2) There are a bunch of unfounded worries about open data collaboration.
The second item is my take on the problems mentioned in the article. Oh yeah, and I think ODC is a really important idea!
by Prof. Per Runeson
😍 (2) The Downfall of the Data Engineer
Maxime Beauchemin is a visionary in the field of data. He doesn’t write much, apparently, he focuses on greeting amazing products. All the more reason to read everything he writes. This piece is best described by one simple quote:
“Modern teams move fast, and whether your organization is engineering-driver, PM-driven or design-driven, and whether it wants to think of itself as data-driven, the data engineer won’t be driving much. “
This post follows up on The Rise of the Data Engineer, a recent post that was an attempt at defining data engineering …
🔮🔮🔮 Data Company Corner 🔮🔮🔮
Stuff that might be interesting for anyone at the front line of the data world, inside a data company, inspired by much positive feedback from my article on commercial open source software data companies.
📣 (3) From Sven: How to Build the Next Mega OS Project
Remember my argument that the data space will be dominated by open-source pretty soon? Well, so then the next question is, how does one create the next mega OS project. I took a stab at that question with a 3-dimensional model.
The key idea is that most people think it’s just a one-dimensional “make the project” big thing and that there are really only two things you have to do to make that happen.
I argue, there are three different dimensions a project can extend into. Only a 3-dimensional project will be truly successful, and each dimension needs vastly different growth as well as monetization strategies.
How To Build the Next Mega Open Source Project. 8 lessons learned from a 3-dimensional framework for understanding how to turn your open-source project into the next WordPress or Linux..
🎄 In Other News & Thanks
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P.S.: I share things that matter, not the most recent ones. I share books, research papers, and tools. I try to provide a simple way of understanding all these things. I tend to be opinionated. You can always hit the unsubscribe button!
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