Hey, love the idea. I usually start by pinning down the data’s “natural” shape – get a schema that every stream can map to, even if the source is a mess. Then I build a lightweight pipeline that pulls, cleans, and normalises each feed, tagging it with timestamps and provenance. Once the raw bits are in a common form, I feed them into small, self‑contained widgets that know just one thing: display a metric. The whole interface stays modular so you can drag, drop, or swap a panel without touching the others. And if a data source hiccups, I log it and let the widget show a warning instead of breaking the whole board. Keeps the chaos in check, the patterns visible, and the codebase tidy.