What Feature Engineering Means for Analysts

This opening lesson defines feature engineering from an analyst's point of view: turning raw business data into variables that make patterns easier to measure, compare, and model. It explains why feature engineering is not only a data science task, but also a practical analytical discipline grounded in business logic, data quality, and careful measurement.

Learners will distinguish raw fields from engineered features, recognize common feature types, understand how features connect business questions to model behavior, and learn the core responsibilities analysts carry before handing data to a model or dashboard.