This work demonstrates the use of a voltammetric electronic tongue formed by five modified graphite-epoxy electrodes in the qualitative and quantitative analysis of cava wines. The different samples were analyzed using cyclic voltammetry without any sample pretreatment. Recorded data were evaluated by Principal Component Analysis and Discrete Wavelet Transform in order to compress and extract significant features from the voltammetric signals. The preprocessed information was evaluated by an Artificial Neural Network that accomplishes the qualitative classification. Moreover, a preliminary study related to the quantification of sugar amount present was assessed by Second-Order Standard Addition Method.