Just a quick one—I’m running a short survey to see what topics you’d like more of in the newsletter. It’ll help me keep things exciting and valuable for you!
If your desired topic isn’t listed, just let me know in the comments! 😊
Wow, thank you so much! For my research process, I usually start by choosing a topic that I believe will bring value. Then, I dig into related videos, papers, books, and code repositories. After gathering enough information, I create an outline for the article, which typically takes me about 3-4 days. If I need to dive deep into the source code, the research might take longer.
When it comes to writing, I put myself in the reader's shoes and continuously revise and rearrange my writing to make it as simple and clear as possible. I also avoid using jargon whenever I can.
For illustrations, I try to visualize what I want to depict as I write and jot down ideas along the way. Once the text is finished, I dedicate 1-2 days to creating all the illustrations based on those notes.
I agree , Vu Trinh’s ability to explain complex technical details in simple steps complete with illustrations is quite remarkable.
My thoughts on this is, you need to read an awful lot on the subject and try to explain it with pictures. You need to dig into the details but summaries and distill the core concepts.
You need to simplify.
Quote from Einstein: “Make things as simple as possible and no simpler”.
It’s a rare talent that takes years of experience (and failure, and getting up afterwards).
That’s my view.
You can read my thoughts on Snowflake at “Analytics Today “. Or read all 30+ articles at
No specific company or tool per se. I just think it would be good to get an overview of how recent, broad innovations across the stack (e.g. Rust-based tooling, Ibis, s3 express one zone, etc.) might redefine the traditional approach a lot of DEs take. Most of the blogs that devs post are for like petabyte scale systems at Canva or Discord.
I guess another way to look at it would be: which recent innovations in the space should normie DEs consider paying more attention to/swapping into their stack?
Hey Vin! I’d be interested in your thoughts on Snowflake, perhaps even a Snowflake Vs Databricks or either Vs. Open source (eg.Apache Stack) for Data Engineering and Analytics.
Thank you for the suggestion! However, I don’t plan on writing an article about LLMs anytime soon, as I don’t have any experience or knowledge in AI or machine learning.
I want to know how you are writing articles.
I have been following yt and n number of courses, the way you explain man, that is next level
How you are doing that, Can you write article on the same, or if its there can you share the link
Wow, thank you so much! For my research process, I usually start by choosing a topic that I believe will bring value. Then, I dig into related videos, papers, books, and code repositories. After gathering enough information, I create an outline for the article, which typically takes me about 3-4 days. If I need to dive deep into the source code, the research might take longer.
When it comes to writing, I put myself in the reader's shoes and continuously revise and rearrange my writing to make it as simple and clear as possible. I also avoid using jargon whenever I can.
For illustrations, I try to visualize what I want to depict as I write and jot down ideas along the way. Once the text is finished, I dedicate 1-2 days to creating all the illustrations based on those notes.
I agree , Vu Trinh’s ability to explain complex technical details in simple steps complete with illustrations is quite remarkable.
My thoughts on this is, you need to read an awful lot on the subject and try to explain it with pictures. You need to dig into the details but summaries and distill the core concepts.
You need to simplify.
Quote from Einstein: “Make things as simple as possible and no simpler”.
It’s a rare talent that takes years of experience (and failure, and getting up afterwards).
That’s my view.
You can read my thoughts on Snowflake at “Analytics Today “. Or read all 30+ articles at
Articles.Analytics.Today
Design and architecture of large scale systems
Thank you for your comment ;) I really appreciate it.
Sure, anytime
I’d definitely want to see an article on “modern” stacks for batch systems, real time systems, etc. Ideally not sponsored by a SaaS company 😅
Thanks! Do you have a specific name in mind?
Do you still enjoy a sponsored article that includes a technical deep dive with just a bit of marketing? 😅
I personally find much of what’s written is just marketing nonsense. A technical bullet point list of features and benefits.
I stop reading as an as I see the word “Enterprise” in an article.
I’ve no issue with marketing. But it should come second to real insights. Real education and knowledge transfer.
Yeah, to be clear, I’m not saying you shouldn’t get paid, so def get the bag 🫡
No specific company or tool per se. I just think it would be good to get an overview of how recent, broad innovations across the stack (e.g. Rust-based tooling, Ibis, s3 express one zone, etc.) might redefine the traditional approach a lot of DEs take. Most of the blogs that devs post are for like petabyte scale systems at Canva or Discord.
I guess another way to look at it would be: which recent innovations in the space should normie DEs consider paying more attention to/swapping into their stack?
Thank you so much for your valuable ideas
Thank you for all the great technical deep dives!
Why not sponsored by a SAS company? ;-)
I no longer work for Snowflake, but they have advanced computer technology by 30+ years in the past 5.
Hey Vin! I’d be interested in your thoughts on Snowflake, perhaps even a Snowflake Vs Databricks or either Vs. Open source (eg.Apache Stack) for Data Engineering and Analytics.
I can help short cut the Snowflake research. See
Articles.Analytics.Today
I specialise in Snowflake, but think Databricks is probably a worthy contender along with vendor independent Spark, Trino, etc. etc. on Iceberg.
It’d be interesting to hear your thoughts on these.
Could you do an article about LLMs?
Thank you for the suggestion! However, I don’t plan on writing an article about LLMs anytime soon, as I don’t have any experience or knowledge in AI or machine learning.