My Master's Dissertation: Modern Data Platform with DataOps, Kubernetes, and Cloud-Native Ecosystem

Almost 3 years ago (September 2020), I enrolled in a part-time master's program in data engineering at Edinburgh Napier University. Finally, two weeks ago, I got an email informing me that I successfully completed my master's and the program board of examiners awarded me Master of Science with Distinction in Data Engineering 🎉🎉🎉

My graduation ceremony would have been today, but I postponed it to October 2023 for some personal matters. So it's just a matter of time till the official graduation.

So today, I'd like to share my master's dissertation: Modern Data Platform with DataOps, Kubernetes, and Cloud-Native Ecosystem.

The dissertation builds a proof of concept for the core of Modern Data Platform using DataOps, Kubernetes, and Cloud-Native ecosystem to build a resilient Big Data platform based on Data Lakehouse architecture, which is the basis for Machine Learning (MLOps) and Artificial Intelligence (AIOps).

It was a super challenging topic, given the fact that Data Lakehouse architecture emerged just in 2020! But it was great to dive into it. I've been into data for years, and it's exciting to step up my skills from T-Shaped to Pi-Shaped (DevOps and DataOps) :-)

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Hello, my name is Ahmed AbouZaid and this is my "lite" technical blog!

I'm a passionate DevOps engineer, Cloud/Kubernetes specialist, Free/Open source geek, and an author.

I believe in self CI/CD (Continuous Improvements/Development), also that "the whole is greater than the sum of its parts".

DevOps transformation, automation, data, and metrics are my preferred areas. And I like to help both businesses and people to grow.

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