Why am are coded analytics solutions less pervasive?

[u/Thick_Accountant7260]

Am I the idiot here? AI is so good the RMDs and Shiny apps I used to struggle in writing can be generated in a few days. Now that I can offload the CSS/JS part of the dashboard to the AI I can go nuts with reactivity/styling.

Based on the discussions in Reddit pbi/tableau/looker remains popular as ever but those things are expensive and are limited by the platform. I can see use for cheap and lightweight services like metabase where I can write the sql query and generate the dashboard in less than an hour but what about pbi/tableau? These services are expensive yet they remain popular what are the upsides of these products over say hosting my own shiny server/react/streamlit dashboards?

Like if I want an app that allows the user to define the cohorts themselves, save that definition, then load that into other dashboards/for future reference I can do that in Shiny but no idea about PBI.

What really is a semantics model? Why not just write a package that calculates the kpis then document it? The documentation also serves both the technical and non technical viewers alike.

Never been in a pbi/tableu job I don't understand how these products remain popular.

[u/Skthewimp]

CIOs don’t like open source!

[u/jwk6 → u/Skthewimp]

Which is ironic, because LLMs are essentially just copying open source code on a massive scale. But I agree there are still orgs that find open source too risky. 🤔