Data compression is generally achieved by studying the data and looking for redundant
patterns and probabilities. This is a basic concern of information theory, a branch of
mathematics that was founded by Claude Shannon at Bell Labs. Information theory can be
used to determine the entropy, or information content, of a message. The entropy of a
message describes the minimum amount of space that must be used to fully describe the
message. In general, if the information content of a message is smaller than the existing
representation of the message, the message is compressible.





