Implementation Of Big Data Analytics In Improving Audit Quality And Decision Making Systematic Review In The Period 2018-2024: Systematic Literature Review
DOI:
https://doi.org/10.38035/dijefa.v6i3.4677Keywords:
Big Data Analytics, Audit Quality, Decision Making, Systematic Literature Review, Post-Pandemic Transformation, Audit Efficiency, Risk AssessmentAbstract
This study is a systematic literature review (SLR) that aims to investigate the application of Big Data Analytics (BDA) in improving audit quality and data-driven decision-making processes in sectors affected by the COVID-19 pandemic, such as energy, education, and logistics. Using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method, this study follows the stages of identifying, screening, selecting, and synthesizing literature from various relevant academic sources. Through an analysis of studies published in the period 2018 to 2024, the main findings show that BDA has the potential to improve audit efficiency, accelerate risk identification, and assist in more informed and data-driven decision-making in these sectors. This study also highlights significant gaps in existing research, especially related to the application of BDA in the non-financial sector. Therefore, the results of this study can be an important reference for future research, which aims to fill the knowledge gap on the adoption and implementation of BDA in less frequently discussed sectors, as well as to support broader digital transformation post-pandemic.
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