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The issue of product safety is acute in many countries and companies. To increase the safety of products, we need technologies that allow us to test products and knowledge that will prevent the appearance of harmful substances quickly. Today, biosensor technologies for rapid testing of agricultural products are actively developed in the world. Data mining technologies can provide the discovery of new knowledge about the nature and dependence of external factors of various harmful substances. Also, these technologies make it possible to predict the appearance of certain substances in products. Qualitative forecasting will increase the efficiency of actions to reduce the risk of crop damage. The paper considers the construction of forecasting technology, which includes: system analysis of the subject area, analysis of existing solutions, development of general system architecture, search for data sources, data warehouse development, data integration into the system, search for forecast models, model testing, use of Data methods Mining to find qualitatively new knowledge and hypotheses, test hypotheses, display forecasting results in a user-friendly form. These theses present the current state of work.

information management; data warehouse; real-time data analysis; data mining; OLAP and Data Mining technologies; mycotoxins; biosensors