APPLICATION OF COMPUTER TECHNOLOGIES IN ANALYTICAL DATA PROCESSING

Abstract

The article provides a comprehensive overview of the current state and prospects of using computer technologies in analytical data processing within the context of modern economic activities. The rapid digitalization of business processes and the development of information and communication technologies have fundamentally changed approaches to organizing analytical work in enterprises and institutions. The author emphasizes that the integration of computer tools significantly improves the efficiency, accuracy, and speed of analytical procedures by automating routine operations and enabling deep data analysis. Special attention is paid to the use of spreadsheets as one of the most widespread and accessible tools for data collection, systematization, calculation of key indicators, and visualization of results. The paper also highlights the importance of business intelligence systems (BI) that allow companies to process large volumes of data and present them in a convenient interactive form for informed managerial decision-making. In addition, the study analyzes the role of Big Data technologies, predictive analytics, and artificial intelligence in creating advanced models for forecasting financial results, consumer behavior, and potential business risks. The article outlines the main problems that arise in the process of computerization of analytical work, including information security risks, insufficient professional training of specialists, and the need to modernize regulatory support. The author proposes possible ways to solve these issues, including staff training, the use of cloud solutions, and the gradual transition to integrated ERP systems that combine accounting, planning, and analytical functions into a single digital ecosystem. The findings confirm that the effective use of computer technologies in analytical data processing is a key factor for increasing the competitiveness of enterprises in the conditions of the digital economy and ensuring sustainable development in the long term.