An industrial case study of data compression within the library automation domain is described. A context dependent approach, where the individual records require file-independent compression and expansion, is evaluated. The discussed approach favorably compares against popular compression algorithms. Comparisons were made against commercially available implementations of the conventional compression schemes. The described approach is now in use by The Library Corporation.