Not Just SQL - October '23
A brief introduction
Hello data fans and internet folks in general! I'm really excited to welcome you to the very first post of my newsletter-blog Frankenstein. My name is Constantin Lungu, and I've spent the last ten years working with data: as a Data Analyst, Business Intelligence Developer and Data Engineer. You can think of this page as the next chapter in my data story, and I'm glad you're here to be a part of it!
Growing in Public as a Data Creator - I
Does “building in public” apply to content creation? Or shall I better call it “growing in public” ? In this recurring series, I will be documenting my journey with writing about tech and personal branding.
Let’s start with a little backstory. I’ve always enjoyed writing on topics I care about. Given my line of work, I engage in technical storytelling as well (yes, I sometimes write documentation at work as well).
Origins
In the distant 2016 I was learning Data Analysis with Python while working as a BI Developer. At this stage, I’m just trying just to save the Jupyter notebooks, so I remember how I did this or that.
Fast forward to 2020. Plenty of time during COVID and I make a couple of posts on Medium, sharing stories about my tinkering with Raspberry Pi and how I studied for an AWS Certification. A story like that is a compilation of issues encountered during a long project, so writing an article takes literal weeks. Sharing them to LinkedIn to very little engagement.
Let’s skip another 2 years or so to 2022, when I do another round of posting, this time around practical tips and tricks tied to problems I encounter while working day-to-day with BigQuery. The turnaround is still very slow - preparing an article is tedious and takes days. I submit them to a number of publications in Medium and get a couple of hundred views a month. Again, sharing them to LinkedIn to a dozen or so reactions.
Early 2023, I continue posting a couple of practical BigQuery walkthroughs. I enjoy writing them - straightforward, practical, easy to write. I also find them useful to myself - explaining something in writing helps you understand it better, iron out any issues, get some interesting feedback about something that could’ve been done in a different way. I decide to set up datawise.dev - my blog, hosted on Hashnode. I’m now cross-posting on Medium (with a canonical links).
Things started getting more interesting in August 2023. At this point I have maybe 1800 LinkedIn followers, but 80% of them are recruiters, so engagement on technical content I post is not great.
I was already following some big creators in the Data world, but I discovered the Creator Mode on LinkedIn and started paying attention to audience as well (before, I used to think only in terms of engagement - comments, reactions, re-posts).
One Friday in August, before leaving for the weekend, I wrote a short post about the ROLLUP command in BigQuery, which I found interesting since I never had to use it.
I was very surprised to see that it received ~270 reactions, easily more than the sum of all the reactions to my previous posts. Here’s the post.
At this moment, I start to get a little bit more interested about how LinkedIn works in general - I learn that the time you post matters, outbound links get posts penalized, engagement in comments matters, nice images boost distribution and so on.
I decided to continue writing short, condensed, reproducible examples inspired by my Data Engineering practice, along the following lines:
problem scenario → possible solution
new or less known feature → use cases
comparison of alternatives → pros & cons and when to use which
It’s October 2023 and I decide to set up this domain and a Substack presence, although my idea about the format is not very precise yet 😊.
Current situation
I strive to write 3-5 times per week, and I have been consistently doing so for the last 10 weeks. There are some promising numbers around content performance and the Medium numbers have never been higher. I’ve also managed to surpass 3k followers on LinkedIn, most of them new followers based on my posts.
There is of course a great deal of variability in the content performance, due to an array of factors I’m analyzing at the moment - stay tuned for more here. Here’s a screenshot of the correlation matrix I’ve asked my data analyst - ChatGPT - to build with the data I’ve collected so far on my LinkedIn posts.
What’s next
It’s of course a little hard to see the future, but I’m eyeing the following next steps:
refine content: more value in a concise format that I would like to experiment with
analytics: find out what works best and use it to grow
more polish: a little bit of marketing magic applied to the content
diversification: write about more diverse topics that just BigQuery
personal projects: engage with new technologies and explore them for myself and my audience
Things I’ve followed 👉
One of the hottest debates in tech (and on LinkedIn) this month was around Indian top executive statement that youth should be looking at 70-hour work weeks for their country’s economic advancement. I’ve also read about 9-9-6 work schedule and the Protestant Work Ethic while at it.
OpenAI’s ChatGPT new release adds support for DALL-E3 , so you can now generate interesting right there. I think I’m going to write a post-apocalyptic retro-futuristic novel with illustrations like the below
Content Recap
Here’s an overview of my articles released in October on my blog - Datawise.
SQL 📰
Python
Not really about data
Here are things not really related to data or tech, but that I enjoyed reading about in the last month:
Silbo Gomero - a whistling language spoken (whistled) on La Gomera island of the Canaries
Soundex - a phonetic way of indexing names by their sounding in English
Soft serve - didn’t know this type of ice cream has its own name