We present a framework for KDD process implemented using SQL procedures, consisting of constructing new attributes, finding rough set-based reducts and inducing decision trees. We focus particularly on attribute reduction, which is important especially for high-dimensional data sets. The main technical contribution of this paper is a complete framework for calculating short reducts using SQL queries on data stored in a relational form, without a need of any external tools generating or

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... their syntax. A case study of large real-world data is presented. The paper also recalls some other examples of SQL-based data mining implementations. The experimental results are based on the usage of Infobright's analytic RDBMS, whose performance characteristics perfectly fit the requirements of presented algorithms.