FNT502

Articles

The article presents a comparative analysis of theoretical approaches to data analytics and decision-making in the financial sectors of Africa and the United States, highlighting how economic, technological, and regulatory differences shape their adoption and implementation. In the U.S., advanced infrastructure and regulatory frameworks facilitate the integration of models like the Efficient Market Hypothesis, Behavioral Finance, and Portfolio Theory, supporting sophisticated financial strategies. Conversely, Africa's financial sector, characterized by diverse and emerging markets, innovatively adapts these theories to address challenges such as limited data and infrastructure, with a focus on mobile banking and financial inclusion. The paper underscores cultural and economic influences on theoretical preferences and offers practical recommendations for policymakers to enhance data analytics and decision-making, including improving data quality, fostering innovation, and supporting financial education. It concludes by emphasizing the need for continued research to validate and adapt these approaches, ensuring their relevance in evolving global financial landscapes.

This article explores the transformative integration of Big Data, Artificial Intelligence (AI), and the Internet of Things (IoT) in enhancing business intelligence (BI). It highlights how these technologies synergize to enable advanced data analysis, real-time decision-making, and operational efficiency. Big Data analytics uncovers hidden patterns and trends, AI provides predictive algorithms and machine learning capabilities, while IoT generates continuous, real-time data from interconnected devices. The study proposes a comprehensive framework for integrating these technologies, emphasizing real-time analytics via edge computing, data security through blockchain, and automated workflows powered by AI insights. Additionally, the article discusses emerging trends such as quantum computing and ethical AI practices, which promise to further revolutionize BI by enhancing data accuracy, optimizing decision-making, and fostering trust. The integration of these technologies positions businesses to harness actionable insights, drive innovation, and maintain a competitive edge in a rapidly evolving digital landscape.

This article provides a comprehensive exploration of how dashboards revolutionize these processes. The article demonstrates how dashboards aggregate and visualize complex financial data, transforming it into actionable insights that enable finance professionals to identify trends, monitor performance metrics, and make data-driven decisions swiftly. By offering real-time updates on key financial indicators, dashboards empower organizations to proactively manage risks such as market volatility or liquidity issues, safeguarding assets and maintaining stakeholder trust. Their efficiency in simplifying data analysis and their adaptability to specific roles and institutional needs make dashboards indispensable tools in diverse financial contexts. The article also highlights the predictive capabilities of advanced dashboards, which leverage historical data to forecast trends, allowing organizations to anticipate market shifts, optimize resource allocation, and stay competitive. Furthermore, dashboards promote transparency and accountability by centralizing financial data and fostering collaboration across teams and departments. By reading this article, finance professionals can gain valuable insights into leveraging dashboards to enhance efficiency, foster innovation, and drive success in an increasingly dynamic and data-driven financial landscape.

The article, Embedding Digital Data Storytelling in Introductory Data Science Course: An Inter-Institutional Transdisciplinary Pilot Study offers an innovative approach to data science education by integrating digital data storytelling into project-based learning. It highlights the transformative potential of combining technical skills with communication and storytelling techniques to address real-world sustainability issues. Readers will gain insights into how this approach not only enhances students' technical and analytical capabilities but also fosters cross-disciplinary collaboration and social responsibility. The study demonstrates how collaboration between students from STEM and non-STEM backgrounds can improve communication skills, creativity, and empathy—critical for addressing complex societal challenges. By embedding themes of sustainability and human flourishing, the article emphasizes the importance of using data science as a tool for positive societal impact. Whether you're an educator, policymaker, or data professional, this article provides a compelling framework for designing inclusive, interdisciplinary, and impactful data science programs. It underscores the importance of preparing a diverse workforce capable of using data storytelling to drive meaningful change.