Why not use Excel?
You could just as easily use Excel to answer the same question, and if the goal is to learn how to use a tool, then either tool would be great! But what if you are working on a question where your analysis matters? Maybe you are working with human clinical data trying to diagnose a set of symptoms, or you are working on research that will eventually be published and maybe earn you a Nobel Prize?
In these cases your analysis, and the ability to reproduce it exactly, is vitally important, and Excel won’t help you here. It doesn’t track changes and it offers very little insight to others on how you got from your initial data to your conclusions.
Galaxy, on the other hand, automatically records every step of your analysis. And when you are done, you can share your analysis with anyone. You can even include a link to it in a paper (or your acceptance speech). In addition, you can create a reusable workflow from your analysis that others (or yourself) can use on other datasets.
Another challenge with spreadsheet programs is that they don’t scale to support next generation sequencing (NGS) datasets, a common type of data in genomics, and which often reach gigabytes or even terabytes in size. Excel has been used for large datasets, but you’ll often find that learning a new tool gives you significantly more ability to scale up, and scale out your analyses.