The Use of Big Data in Corporate Accounting and Data Analysis: Opportunities and Challenges

Introduction: the era of Big Data technologies is restructuring corporate accounting, enabling a wide array of dynamic potential. This project explores how Big Data affects financial management, focusing on forecasting, risk management, and technological advances. Method: this work is informed by a large-scale review of scholarly literature, industry reports, and case studies. Databases like Google Scholar, PubMed, IEEE Xplore, Scopus, and Web of Science were used for data collection. Keywords included Big Data, corporate accounting, financial forecasting, risk management, data analytics, AI in accounting, machine learning in finance, and blockchain technology applied to accounting. The review was structured thematically, focusing on financial forecasting, risk management, and ethical considerations affected by Big Data practices in this domain. Results: Big Data improves financial forecasting accuracy using historical data, market trends, and consumer behavior analytics. In risk management, Big Data facilitates effective proactive actions through thorough risk evaluation. Emerging technologies are anticipated to automate complex tasks, enhance predictive analytics, and improve the security and reliability of financial transactions. Conclusions: Big Data holds significant potential for corporate accounting, though challenges such as managerial complexity, data privacy, and expertise requirements for handling large volumes of data remain. The study highlights the importance of flexibility and technological adaptability, as well as specialized skill sets. It calls for continual dialogue and policy development to meet the ethical challenges presented by Big Data/AI, promoting responsible deployment while ensuring fairness. This review contributes to academic discourse and provides strategic guidance for practitioners in the evolving landscape of corporate accounting