Power Bi and Data Analytics in Financial Reporting: A Review of Real-Time Dashboarding and Predictive Business Intelligence Tools

This systematic review explores the transformative role of Power BI and modern data analytics tools in reshaping the domain of financial reporting. In an era where organizations are increasingly prioritizing real-time decision-making, predictive insights, and compliance automation, the integration of business intelligence (BI) platforms into financial workflows has become both a strategic imperative and a technological necessity. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, this review critically analyzes 61 peer-reviewed studies published between 2010 and 2025, sourced from academic databases such as Scopus, Web of Science, IEEE Xplore, and Google Scholar. The review identifies eight core thematic areas: technological foundations of BI in finance, real-time dashboarding, predictive analytics integration, performance measurement, regulatory compliance, data pipeline architecture, organizational adoption, and theoretical-methodological insights. The findings reveal that Power BI is widely adopted across industries for streamlining financial disclosures, enabling interactive dashboards, and integrating predictive modeling capabilities through R, Python, and Azure Machine Learning. Furthermore, the review highlights how self-service analytics, automation of ETL pipelines, and real-time KPI tracking have enhanced both the operational efficiency and strategic agility of finance departments. In addition, the study uncovers common barriers such as skill gaps, resistance to change, and fragmentation in data governance. By comparing the reviewed findings with prior literature, the paper presents an updated understanding of how Power BI is transitioning from a reporting tool to a core financial intelligence system. The study concludes with targeted recommendations for practitioners, researchers, and policymakers to maximize the benefits of business intelligence in financial reporting, while also identifying areas for future inquiry, including longitudinal impacts, ethical considerations, and cross-industry comparisons.