DATA VALIDATION IN THE RESEARCH OF LOGISTIC SYSTEMS OF AGRO-TRADING IN UKRAINE

The article addresses the pressing issue of developing validation data sets to assess the state of the logistics system in Ukrainian agro-trading under turbulent conditions. The study explores the concept of «validation» as it applies across various domains, such as law, manufacturing, and programming, emphasizing its critical role as a mechanism for verifying information quality. The principles and procedural stages of forming validation data sets are substantiated, starting with collecting primary and secondary statistical data, followed by systematization, analysis, and interpretation. Particular attention is paid to ensuring the reliability and representativeness of information, with detailed approaches to identifying errors in data registration and implementing source monitoring practices. The article also emphasizes the importance of accurate and systematic data validation in improving analytical models. Valid data sets enable precise risk assessment and provide actionable insights, supporting robust management decision-making. Given agro-tradingʼs dynamic and often volatile environment, integrating reliable data is a key factor in addressing challenges such as supply chain disruptions, resource allocation inefficiencies, and external economic pressures. Furthermore, the article underscores the role of validation in enhancing the transparency and accountability of logistics processes, contributing to the overall resilience of agro-trading enterprises. By adhering to validated information frameworks, stakeholders can better anticipate risks, optimize operations, and align with international standards. The proposed methodological approaches and validation criteria provide a practical basis for improving decision-making in the logistics systems of Ukrainian agro-trading, fostering sustainable growth and competitive advantage under challenging conditions.