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Recent efforts to support analytical tasks over relational sources have pointed out the necessity to come up with flexible, powerful means for analyzing the issued queries and exploit them in decision-oriented processes (such as query recommendation or physical tuning). Issued queries should be decomposed, stored and manipulated in a dedicated subsystem. With this aim, we present a novel approach for representing SQL analytical queries in terms of a multidimensional algebra, which better characterizes the analytical efforts of the user. In this paper we discuss how an SQL query can be formulated as a multidimensional algebraic characterization. Then, we discuss how to normalize them in order to bridge (i.e., collapse) several SQL queries into a single characterization (representing the analytical session), according to their logical connections.