Data streams are one of the most relevant new data sources, they refer to flows of data that come at a very high rate. Let us consider a stock-exchange market, where n different stocks with p considered attributes (e.g. price, quantity, seller/buyer id, . . .) are negotiated all day long. The distinguishing feature in data streams analysis is that the focus is on transient relations. The present paper proposes a visualization tool exploiting Multidimensional Data Analisis (MDA) techniques to represent the evolving association structures among attributes over different time-frames. The general aim is to detect the stability of the deviation from indipendence in the occurrence of an observed set of attributes stored as binary stream.