In this paper an Information and Communication Technology (ICT) prototype of Big Data Analysis System based on Data Mining Techniques, Hadoop information infrastructure platform for distributed data collection and MATLAB analytical environment have were proposed. The obtained results of test activities related to some system modules for clustering analysis, recognition and classification tasks about defined economic objectives and processes are presented. Achieved indicators for revenues, expenditures and procedures for excessive deficit for individual Economic regions in Europe, covering the period from 1995 to 2021, according to a report by the European Commission were defined as a complex object of study. Approaches based on k-Means Clustering, Linear and Quadratic Discriminant Analysis, Resubstitution and Cross-validation Techniques, Feed-Forward Neural Networks (FFNN) with Scaled Conjugate Gradient training algorithm were applied. Models with observed high quality indicators were synthesized in the process of the exposed procedures.

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