Authors - Anudeep Arora, Ranjeeta Kaur, Neha Tomer, Vibha Soni, Neha Arora, Anil Kumar Gupta, Lida Mariam George, Prashant Vats Abstract - The incorporation of data analytics into internal audit operations is a noteworthy progression in augmenting the efficacy and productivity of audits. In this paradigm, strategic analysis refers to using data-driven insights to evaluate risks, expedite audit procedures, and enhance organizational controls. This article examines the use of strategic analysis in data analytics and internal audits, including important techniques, advantages, and difficulties. It talks about how sophisticated data analytics methods, such as machine learning, statistical analysis, and visualization software, can change the way that auditing is done today. In addition, the paper looks at case studies and potential future developments in the subject, giving readers a thorough understanding of the various ways internal auditors might use data analytics to provide audit results that are more precise and useful.
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