The active use of test automation approaches in software development causes further automation of this process, in particular, in the field of results analysis. This monograph presents the results of applying the methodology for creating information technologies of multi-level intelligent monitoring to provide data for decision-making processes by a testing engineer. Methods of text mining and machine learning are combined to build a methodology for creating intelligent multi level monitoring systems. The classification of these data was provided using an ensemble of models, where the resulting value was obtained combining predictions by meta-learning using stacking. The main methods of data analysis and processing in the field of decision-making systems and competitive analysis are analyzed.