Abstract
The agro-industrial sector, like other industries, is increasingly data-driven and data-analytical. From crop selection to assessing consumer food preferences, data is collected at every stage of the agricultural chain. The huge amounts of data collected and processed have already fundamentally changed the structure and efficiency of various agricultural production and supply systems. Modern digital technologies are being actively introduced into agriculture, from laboratory conditions to open and protected fields. The use of machine learning tools, robotics and big data technologies significantly transforms and optimizes not only production processes, but also methodological approaches for scientific research. The results of the study suggest that the use of big data sources in addition to statistical observations helps to reduce the burden on respondents, which is an important task for national statistical services.
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