Overview
This Excel mini series is my third project on this website and part of my portfolio. It consists of several smaller projects, all built to teach me how to use Excel effectively.
Why Excel?
I was collecting data on skills required to land a data analyst role — that was going to be my third project. But it ended up taking a backseat because recent opportunities and job listings kept emphasising Excel. It turns out that to become a data analyst, the most important technical skill you need is Excel, above everything else.
I will release that fourth project once I have enough Excel experience under my belt. Excel isn't the only skill out there, and it might help other aspiring analysts see what they should focus on.
Excel challenges
After working primarily on Linux with terminal-based workflows, GUIs in general have become frustrating and slow. They feel sluggish for creating and analysing data compared to tools like Python, pandas, and other libraries.
That said, most of the working world relies on user interfaces designed for ease of use. I feel like I've had to reverse my optimal data-handling workflow just to meet employer expectations — once I land a data analyst role, I can evolve more efficiently by processing these Excel sheets in pandas instead.
To be fair, I don't have enough internalised syntax memory for pandas, Plotly, and other libraries to handle .xlsx files efficiently in Python without Excel at the moment. The time I spend away from those libraries won't help my goal of becoming a data engineer, but getting the role comes first.