Appreciate the effort. would definitely try this project personally. But can you come up with full data engg architecture that companies actually use. For example companies like uber,lyft,doordash etc. I would like to see how they design their data architecture to process huge volume of data 24*7. right from types of data collected to visualisation. Also pls try to include industry standard tools like airflow even though there are many simpler alternatives to airflow like mage ai. Cause many of the interviewees seek for these regardless of any better tools u know. Hope u found this review useful. Big fan ❤
@CodeWithYu
Күн бұрын
Thanks for the feedback! ❤
@Ahmed-lt6rr
17 сағат бұрын
If I am a beginner, Can I study on your platform or I need pre requisites ?
@Vilayat_Khan
Күн бұрын
u could upload the dataset too ))) please do it!
@yash-ri2lg
Күн бұрын
why use quix and not strucutured streaming, I have read the document that quix is python based but does quix qualify for industry grade projects?
@CodeWithYu
Күн бұрын
Quix is absolutely suitable for production applications. In fact, it’s already being used by Formula 1 racing teams and major energy companies, where real-time insights from high-volume telemetry data are critical to their operations.
@yash-ri2lg
Күн бұрын
@@CodeWithYu but what's the difference between using quix and structured streaming?
@CodeWithYu
20 сағат бұрын
@@yash-ri2lgWhile they share some similarities, they’re fundamentally different. Quix isn’t necessarily a direct drop-in replacement for Spark Structured Streaming, but it can definitely serve as a strong alternative depending on your use case
@nagaharshavardhan8778
14 күн бұрын
Bro this are real time projects that data engineer do
@CodeWithYu
5 күн бұрын
Definitely! Don’t forget to like and share!
@Vilayat_Khan
Күн бұрын
where is github code? is it free?
@CodeWithYu
Күн бұрын
It’s available on GitHub. Link in the description.
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