With just the tidyverse library (which includes dplyr), R can be very useful in a data analysis pipeline. It is great for data cleaning and aggregation, especially when a process needs to be done multiple times. It is much faster than excel/power query. I am an accountant in SaaS and spend a lot of my day waiting for excel/powerbi automations to refresh. Similar solutions in R/sql/python would be nearly instant. Also excel/powerbi automations are a bitch to troubleshoot, and are unnecessarily complex.

When following tidy principles, a framework designed by the tidyverse dev Hadley Wickham, R code can be very easy to interpret, similar to SQL. Additionally the R community has made libraries for everything, and I consider R a great general purpose language as well.