People are wedded to Excel because they've spent a lot of time learning it and don't want their skills to become obsolete.
The resistance is rooted in psychological / political reasons, not technical ones.
The resistance is rooted in psychological / political reasons, not technical ones.
Or is your aversion mostly to the M- word?
I find it funny that when it comes to vi vs emacs (or any such similarly geek-approved thing), fans of each will jump up in arms about the precise reason their platform is better, but the same kind of people would not want to take hundreds of thousands of business professionals at their word about why they like using a particular piece of software.
Also office workers can't always be trusted to even plug things in let alone properly assess what an optimal solution looks like.
People used to use Excel to run regression, visualize data, etc. which I consider inferior to R / Python.
I can't speak about other uses of Excel, e.g. financial modeling, insurance.
Excel, 1-2-3, Visicalc are, taxonomically speaking, in the same class.
We have a new order of tools. While they have their own inherent risks, they reflect literally decades of thinking about the risks and limitations of tools whose lineage traces back to Visicalc.
Macro management and security, versioning, distributed access, multidimensionality; all are addressed in a handful of ways with Alpha, Tableau, Looker and other progressive tools.
Excel, floppies, line printers; relics.
Excel is faster to get started. But for advanced tasks, the time it takes to learn Excel / R is about the same.
A big reason why people don't make the leap is because they already spent too much time becoming an Excel expert. Indeed, for young analysts with no baggage, a lot of people learn and use R instead.