“Real analytical work” is the ultimate power-tools-injure scenario with excel, and that’s why this article exists.
Programmers using actual databases and crafting custom analysis do not have this problem. There is a time and a place for excel, and this ain’t it; leave it to secretaries and people trying to copy data into word documents. I like a pivot table as much as the next guy, but JFC, learn to program, learn git, write in latex, publish science.
I’m as much of an R fangirl as the next lady, but still scientists come from any number of technical skill sets. Hardcore analytics is probably gonna flounder in excel, but if you can’t convince IT to let you have something better you can throw together some chi square test or an anova to get an analysis of your data. And often that will be enough.
Excel just isn’t a database (evidenced by the fact that Microsoft also has Access) and it also just isn’t a one stop shop for analytics. Having spent 17 years in academia, I’m well aware that people are resistant to learning new things and also aware that sometimes you NEED to.
Sure you can do some line fitting and sensitivity analysis stuff and that is great for preliminary work, but excel is just not the one stop shop people want it to be. PowerPoint is also turing complete, but just because you can doesn’t mean you should program with it.
The fact that the month rename problem is killing scientific data is just a smell related to the fact that sometimes you’ve got to stop and ask yourself “what am I trying to do” and “what tool should I be using to do it”.
IMO excel should be left to the MBAs and management: if you are smart enough to do set up analysis of variance or run a t-test or have an intelligent discussion about p values, you SHOULD NOT be dependent on excel.
