Critical Information where you need it, when you need it.
Next Step: ML
Looking at 20 Diagrams at once all day long may result in missing the obvious.
PLus, in many cases, significance is the data that is not shown.
Also, most of the time data have hidden dependencies.
A simple regression on the current dataset (list of recordsets, actually) could define a baseline to indicate what might be important and what not.
- AV Body Temperature might be higher in Arizona, thus no reason for a smart-watch to alert a fever outbreak. (just made this one up, need to verify)
ML would reveal such things,
Yamanu has 100 ML algorithms built-in, that can be used - on any Smart-Dataset.