Comment by openrisk
Comment by openrisk 2 days ago
The bigger picture is the "democratization" of data science [1], not as an academic pursuit by white coat researchers (which was the main early use case for R) but embedded in day-to-day operations in organizations of all sizes. "Apps" (web or mobile) is how this embedding is done. Reactivity is an important consideration when deploying a complex screen with many visible data elements and visualizations.
The problem is how to increase the efficiency with which back-end developments (by technical people) get rolled-out to the end-user base. There are countless ways to do this of-course. The more technical resources one has available (e.g. knowledge of different stacks etc.), the more options. But when resources are scarce one is tempted to look for the (possibly only perceived) efficiency of a "full stack" approach.
[1] a loose term which nevertheless reflects something very real: the widespread use of data in society for all sorts of purposes
Cursed in your view because it’s not Python?