Missing Values and Outlier Handling

Scenario

You are preparing data for a supervised learning task and notice that some features have missing values and a few columns contain extreme observations. You want a preprocessing approach that improves model quality without distorting the underlying signal.

Question

Explain how you handle missing values and outliers during the data preprocessing phase.