Leveraging Big Data Analytics to Improve Decision Accuracy in Business Accounting
Abstract
The rapid evolution of big data technology has significantly transformed business accounting practices, enhancing decision-making accuracy and operational efficiency. This study aims to explore the potential of big data analytics to improve the precision of managerial decisions in accounting, while identifying key implementation challenges and offering strategic recommendations for effective and sustainable adoption. Using a qualitative approach based on a systematic literature review, the research analyzes ten high-impact journal articles published over the past decade. The findings reveal that big data enables real-time processing of vast and diverse data sources—from financial transactions to consumer behavior—supporting more accurate financial forecasting, fraud detection, and risk mitigation. Advanced tools such as machine learning, deep learning, and automated analytics significantly enhance reporting accuracy and transparency. However, challenges remain, including data silos, a lack of analytical skills among accounting professionals, technological infrastructure limitations, data governance issues, and internal resistance to change. Case studies from companies such as IBM, Walmart, and GE illustrate successful implementation when supported by clear digital roadmaps, strong leadership, and a culture of data-driven decision-making. This study bridges the gap between traditional accounting systems and modern data-driven environments and provides practical recommendations for accounting managers, including investing in employee training, fostering a data-driven culture, upgrading technological infrastructure, and addressing data governance through clear policies and frameworks. The findings are expected to assist accounting practitioners and policymakers in developing actionable strategies for integrating big data into accounting frameworks, ensuring its effective and sustainable application.
Keywords: Big data analytics, decision accuracy, business accounting.
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