Reactor relevant experiments for Magnetic Confinement Fusion, like JET, produce already tens of GBytes of data per shot and the next step device, ITER, is expected to require orders of magnitude more. Managing such vast quantities of data in an efficient way needs new techniques, ranging from signal storage and information retrieval to data analysis for physical interpretation. At JET significant efforts are being devoted to all the main issues. Lossless data compression is under development for both mono and bi-dimensional signals, together with new techniques and technologies for image processing (directional wavelets and Cellular Non-linear Networks). Structural pattern recognition has shown great potential for information retrieval. Statistical methods, like Bayesian inference and regression trees, are being systematically investigated, to extract the required knowledge from all the available measurements. Other Soft Computing techniques, like Fuzzy Logic and Artificial Neural Networks, are very powerful tools to handle the great complexity and uncertainties of present day and near future experiments.