A chart that looks too good to be true usually is. A metric climbs for no reason, or a steady trend just stops. Before you base a decision on those numbers, you have to be sceptical and dig into the “why.” I’ll share my process for separating system noise from actual user behaviour. We’ll look at real-life examples of anomalies and discuss how to find the root cause and make the right call when you’ve solved the case, but the data remains messy.
- Business Analytics
- Data Management
