Thanks for the excellent recommendation, I have been through kleppmann's book and it's a must for anyone who wants to be serious about data engineering (or whatever it's called these days). I am looking however for something more practical and less technical, maybe something like projecteuler or cracking the cracking the coding interview but for data
IMHO data eng is too niche and new for that kind of content. But I would love to see if there is anything out there like that.
Is the goal here to get through system design interviews or something like that? You can check out pramp.com if so.
If it’s for learning, then reading some of the original Google papers behind a lot of the big data technologies has been very rewarding for me.
You could try reimplementing the paxos algorithm for example.
Comments
kleppmann’s book: designing data-intensive applications.
It’s very well written, but maybe doesn’t have as much in the way of exercises.
Thanks for the excellent recommendation, I have been through kleppmann's book and it's a must for anyone who wants to be serious about data engineering (or whatever it's called these days). I am looking however for something more practical and less technical, maybe something like projecteuler or cracking the cracking the coding interview but for data
IMHO data eng is too niche and new for that kind of content. But I would love to see if there is anything out there like that.
Is the goal here to get through system design interviews or something like that? You can check out pramp.com if so.
If it’s for learning, then reading some of the original Google papers behind a lot of the big data technologies has been very rewarding for me. You could try reimplementing the paxos algorithm for example.
I am a bit rusty with spark and I have a practical interview where I will be given various datasets to extract insights from them.