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Fuzzy transform is a novel, mathematically well founded soft computing method with many applications. In this paper, we present this technique with applications to data analysis. First, we show how it can be used for detection and characterization of dependencies among attributes. Second, we apply it to mining associations that have a functional character. Moreover, the mined associations are characterized linguistically which means that their antecedent consists of fuzzy numbers and the consequent is characterized using pure evaluative linguistic expressions (i.e. expressions such as small, very big, more or less medium, etc).