There are several ways to enhance available data for improving predictors. Feature extraction adds features (columns) to the data matrix by applying transformations to existing columns. There exist several semi-automatic transformations (e.g., PCA); "manual" feature engineering requires human ingenuity and understanding the data domain and the prediction task. The problems listed below are those in which feature engineering proved to be important.
See feature engineering on Wikipedia.