The process begins by loading the Moving Avgerage Features dataset and applying the Moving Average Features node to calculate rolling averages over defined time windows. These include moving averages for amounts, transactions, sales, and unique users.

The output is an enhanced dataset containing trend-focused metrics that help analyze user activity, seasonality, and long-term behavioral patterns. The Print N Rows node displays the computed features for validation and exploration.

This workflow enables trend-aware data transformation for advanced analytics and time-based modeling.