Factor analysis attempts to explain the features or columns of a dataset in terms of a small number of factors. It is similar to principal component analysis, but uses a slightly different measure to find the best fit.
An early use considered many different kinds of intelligence tests, each of which gave slightly different results. Factor analysis uncovered a smaller number of underlying aspects (verbal intelligence, numeracy, 'general' intelligence, etc.) where each test can be seen as combining these underlying factors with different weightings.
Also used in hcistats2e: Chap. 11: page 131; Chap. 12: page 137