Abstract
This research explores the role of big data analytics in financial reporting decision-making in Kano State, Nigeria. The objectives are to: (1) determine how big data analytics improves the accuracy of financial reports, (2) assess the impact on predictive financial modeling, and (3) evaluate the efficiency gains from using big data analytics. A survey design was chosen to gather data from financial analysts and IT professionals. The sample size, derived using Taro Yamane's formula, ensures representativeness. MTN Nigeria was selected as the case study due to its extensive use of big data analytics. The reliability coefficient score of the survey was 0.89. Findings indicate that big data analytics significantly enhances the accuracy and predictive power of financial reports, leading to better decision-making. It is recommended that companies in Kano State invest in big data analytics tools and training to leverage these benefits in financial reporting.
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Chapter One: Introduction
1.1 Background of the Study
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