As a liberal arts student with little to no prior exposure to data analysis, programming, or complex visualisation tools, I was initially concerned about keeping up with the coursework when I discovered that both semesters included data analysis courses. I felt a strong sense of apprehension.
During the first semester, I learned about Notebook, gaining an understanding of how it helps people organise code and analyse data more efficiently. Although I progressed slowly at first and encountered many errors, I gradually understood the logic behind the code and learned analytical models such as decision trees. In the second semester, the course introduced analytical tools like Python and RawGraphs, and I also learned to use Tableau for interactive analysis.
For example, in RawGraph’s chart analysis, I was able to use an alluvial diagram to examine the relationship between movie genres and return on investment, and a beeswarm plot to observe the revenue distribution of different movie genres. Compared to simply looking at numbers, these visualisation tools allowed me to discover hidden trends and details in the data, which further sparked my interest in data analysis.
Looking back on the entire learning process, from being completely unfamiliar with the subject at the beginning to gradually mastering Python, RawGraphs, Tableau, and even writing my own analysis code, I gained not only technical skills but also confidence in interdisciplinary learning. As long as you are willing to spend time learning, practising, and exploring, data analysis can also become your own tool.
During my studies, I couldn’t help but ask myself: Are these data analysis skills really useful for my future career development? To be honest, after two semesters of study, my skills are still far from those of my peers who specialize in data analysis. However, what is more important is the exploration and discovery I gained during the learning process.
This experience marked an important step in crossing a threshold—from complete unfamiliarity to daring to take action and explore. I have gradually come to understand that data is a tool that can be learned, researched, and continuously improved. In the future, no matter what new fields or skills I encounter, my open-minded attitude and courage to tackle problems will become my core competitive advantages in the workplace.
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