This week in class we focused quite a bit on Microsoft Excel, and how useful it can be in terms of both pure data analysis and for testing the results we receive from our results in R.
As a combined CS & Finance major, this was very interesting to me, as Excel is essentially the main bedrock of most work in the Financial industry. If one were to look at NUCareers for the different jobs available in D'Amore McKim, they would see that the vast, vast majority of jobs like to see students have some experience using Excel. For the most competitive jobs especially, employers like to see students know their formulas and analytics techniques, as these skills can be extremely important for the position. Whether it's making pivot charts to show management, nice graphics to show off to clients, or basic computational algorithms to parse Financial data, Excel is a pivotal part of Finance.
Of course, Finance isn't the only domain where Excel is important. In Marketing Excel is vital for charting trends and analyzing different user data. In politics it's used to keep track of voting trends and constituent data at times. In high school I volunteered on a political campaign for a local state Senator, and they would keep track of everyone who donated money or volunteered through a simple Excel document. If ever someone wanted to learn more while we were canvassing, we would fill out their information on a paper form, and then reenter that data into Excel back at the office. Thankfully that process has been streamlined now, with constituents entering their information on an iPad first, but that data still gets routed to an Excel document, showing how ubiquitous the software is. Even in Chemistry, Excel is useful to organize raw data and perform basic mathematical analysis.
Along with that, Excel is incredibly deep. While other programs do exist that compete, like Google Sheets, none of them are capable of anywhere near the level of calculations that Excel is. Even if we were to ignore VBA code, one can do an incredible amount of analysis on a simple table in Excel. They can parse text, use pivot tables to filter and group data, and even build regression models. Even a simple bar chart comes with a plethora of options for formatting and style.
Essentially, any task that requires some analysis or repetitive calculation can be done quickly and smoothly using Excel. Whether it's for college, work, or a side project, Excel is a vital tool for reporting and analyzing data. Although it's true that there are newer technologies available, practice has shown that Excel is still one of the most reliable and useful of them all.