Implications of Big Data in Accounting: Challenges and Opportunities

Leonidas Theodorakopoulos, Georgios Thanasas, Constantinos Halkiopoulos

Abstract


Objectives: This paper aims to comprehensively explore the implications of Big Data within the realm of accounting, dissecting both its potential advantages and the hurdles it presents. The primary goal is to introduce and delineate the potential benefits of Big Data integration in accounting practices. Additionally, it seeks to identify and thoroughly examine the challenges impeding the seamless assimilation of Big Data into accounting methodologies. By delving into diverse applications, including Auditing, Cost Management, and financial reporting, this study aims to shed light on the multifaceted nature of Big Data's role in accounting. Methods/Analysis: This paper commences with an introduction to the concept of Big Data and its anticipated advantages for accounting practices. It proceeds to conduct a meticulous review and synthesis of existing literature, dissecting the intricate relationship between Big Data and accounting. Through this review, it emphasizes the stumbling blocks encountered in integrating Big Data. Subsequently, it offers a detailed exploration of Big Data's applications in accounting. Findings: Big Data exhibits the potential to substantially transform accounting practices, offering avenues for superior decision-making and analysis. However, the challenges related to data management and analysis pose substantial barriers for accountants in effectively integrating Big Data. Novelty/Improvement: This study offers a comprehensive exploration, dissecting both the potential advantages and challenges presented by Big Data within accounting practices. It provides detailed insights into specific applications of Big Data in accounting, going beyond a surface-level understanding and focusing on domains like Auditing, Cost Management, and financial reporting.

 

Doi: 10.28991/ESJ-2024-08-03-024

Full Text: PDF


Keywords


Big Data Technologies; Accounting; Big Data Tools; Big Data Limitations.

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DOI: 10.28991/ESJ-2024-08-03-024

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