In this blog, we have discussed data compression more than once, but not really about its philosophy. Data compression is seen as an “enabling technology”—a technology helping make things happen—but what makes it so interesting is that it ultimately gives us insights into the very nature of data, of information itself.
Data compression is not, however, simply about “dropping redundant bits” (although it’s a great way of putting it in order to dismiss the matter with non-technical people), because bits very rarely just stand there being very conspicuously redundant1. No, data compression is about transforming the data into a representation in which there is, after analysis, exploitable redundancy.
Recently, I gave a talk at the LISA, Université de Montréal, entitled Compression 101, introducing the main concepts of data compression, stressing on points I find particularly important.