If you guys want to learn more about data engineering, then sign up for my newsletter here seattledataguy.substack.com/ or join the discord here discord.gg/2yRJq7Eg3k
Main of the vocabularies mentioned in this video. 1. CDC: capture data change 2. Normlization/denormalization 3. Pubisher/Subscriber AKA Producer/Comsumer 4. Execution plan 5. Data lineage 6. Data governance
Seattle Data Guy - Love the quick summaries of key concepts here! The pictures of the different types of normal forms are a great way to communicate the concepts
Crazy that you've uploaded this today having watched your previous video on this yesterday and binging your other data engineering videos in the last week. Love the content!
Hey, tnx for the video, love your content. You mentioned some links regarding the "Execution plan", but I can't find them in your description. Also, I would like to learn more about data governance, I am most interested in ensuring data we store is high-quality data. So any links are very appreciated. :) At my work, I learned that if a mobile app has any kind of bug and therefore analytics data is not collected properly, that incomplete data stays forever in our warehouse. So I would like to introduce some sort of system that makes sure that we store complete and high-quality data. Also, I would like to if the data is not complete that someone gets an email with details.
If you guys want to learn more about data engineering, then sign up for my newsletter here seattledataguy.substack.com/ or join the discord here discord.gg/2yRJq7Eg3k
Main of the vocabularies mentioned in this video.
1. CDC: capture data change
2. Normlization/denormalization
3. Pubisher/Subscriber AKA Producer/Comsumer
4. Execution plan
5. Data lineage
6. Data governance
Seattle Data Guy - Love the quick summaries of key concepts here! The pictures of the different types of normal forms are a great way to communicate the concepts
Glad it was helpful!
Crazy that you've uploaded this today having watched your previous video on this yesterday and binging your other data engineering videos in the last week. Love the content!
Thanks for all the support! Trying to keep putting stuff out! Actually at a conference right now so I am juggling a few things 😂
Thanks. Those were great topics to be prepped for when interviewed.
thanks! Was interested in the field, still not in college so looking forward to it. Good to start early & prep for future :)
How you are so great with your concepts. 😅
Inspiring us to work hard
I asked myself the same thing 😅
+9999999999999999
Thank you so much 😀 happy to help!
Love the content! Explanations are pretty simple which has really helped me understand few things.
Thanks !
Great to hear!
Looking buff, boi!
hahaha thanks...
Debezium is also a good example for CDC
Love the Ken Jee Merch
Hey, tnx for the video, love your content. You mentioned some links regarding the "Execution plan", but I can't find them in your description.
Also, I would like to learn more about data governance, I am most interested in ensuring data we store is high-quality data. So any links are very appreciated. :)
At my work, I learned that if a mobile app has any kind of bug and therefore analytics data is not collected properly, that incomplete data stays forever in our warehouse. So I would like to introduce some sort of system that makes sure that we store complete and high-quality data. Also, I would like to if the data is not complete that someone gets an email with details.