End-of-Year Report on a 12-Year Data Journey
Introduction: Beyond Numbers
In my previous position, I created end-of-year reports for my business colleagues and CEOs.
Nothing special, you would say. Standard reports with a bunch of numbers per different business areas—from general business controlling, marketing to supply chain management and finance.
True, and I was aware these reports were part of my tasks and would not draw much attention from every colleague in the company.
So, I gave it some thought on how to make the reports more "attention-getters". The answer was simple—make them sound cool.
In other words, I decided to spice up the report names, as spicing up the numbers was not an option.
The difference between any other standard end-of-year report and "mine" was that I named mine after the trending buzzwords this year.
With this said, the 2020 report was named "The Notorious 2020". The 2021 report was named "The Vax 2021", and the 2022 report was "The ChatGPT 2022".
You already have a clear idea of why I decided on these names.
From the world-turbulent year 2020, when the world was affected by the coronavirus, to the vaccination creation in 2021, and to one of the greatest developments in the data world in 2022—the generative AI chatbot launch.
To move on from the end-of-year business reports, I (finally) decided to create a personal end-of-year report on my career progress.
Why, you ask?
The first reason is that 2023 was the year that marked 12 years of my career, and it was—let's put it like this—transformational. In the sense that I again changed the country, the job, and the living environment at once.
The second reason is that 2023 was one of the biggest years of new technological development since I started my career, and the knowledge barrier for entering the data area has increased.
With all the new developments and sudden demands on generative AI skills in the data field, I think it's one of the most challenging times to start a career.
To confirm this statement, I will just add that even a pioneer of machine learning, Andrew Ng, recently wrote a memo on how to build a career in AI [1].
It's little to mention how this memo is truly inspirational.
Not only does it encourage people to enter the field of AI, but it also gives advice on which skills are required and how to overcome your internal "human" struggles when searching for a job or switching career paths.
Although I can't fully understand how challenging it is to start a data career nowadays, I was able to "find myself" in most of the challenges Andrew described in the memo.
In other words, I know how tricky it is to start building a data career if you didn't explicitly study this area. The feeling of not knowing where to start, what to learn first, or how to develop is well-known to me.
This is exactly the second main reason I finally decided to write this blog post and sum up the "insights" I gathered in the past 12 years of my career.
With this post, my goal is to help someone "out there" with their data career struggles and make new joiners feel encouraged to enter this area. I aim to humanize this process by sharing my stories and a few lessons learned on the path of building a data career.
And now the same old question has arisen: How to name the report to sound cool?
Again, having in mind that 2023 is the year that marked 12 years of my career, I only thought the appropriate name for the report would be "The Cosmic 2023".
So, let me share with you the journey that shaped me as a data professional and made me decide to build, and stick to, a career in the most amazing field ever—the data field.
The Cosmic 2023: The 3 Stories with Input-Output Flow
As the title of the section states, I will share with you three stories that mark the main stages of my professional data journey.
Story one, named "Per Aspera ad Astra", is a story of how I started a data journey. And how you probably shouldn't.
