How do you stop overlapping data from lying to your users?

I’m a solo dev, and I recently ran into a massive data architecture problem while building a personal tracking tool.

I originally tried using standard habit and symptom trackers, but I realized they almost all fail when dealing with overlapping data: situations where one event or routine completely masks the effect of another.

If Input A causes a negative reaction, but I immediately apply Treatment B to cover it up, the raw data simply logs that "Input A led to zero issues." The app basically lies to the user because it treats every log in isolation and can't separate the overlapping variables.

To solve my own problem, I had to stop using generic trackers and build a statistical model (using Elastic Net regression) in the background to calculate true correlations and filter out the noise.

I’m curious how other makers and SaaS founders handle complex, overlapping data points in their products:

• How do you handle overlapping data or hidden variables in your own builds?

• Do you run statistical models in the background to calculate true correlations for the user, or do you just show raw charts?

• How do you design a UI that captures complex context without burning out the user?

Would love to hear how you all approach data context in your own apps!