The financial services industry is experiencing a significant transformation driven by big data technologies and advanced analytics. This article examines how financial institutions are adapting their infrastructure, talent strategies, and operational frameworks to effectively leverage data-driven insights. It explores the critical components of robust data architecture, including cloud computing, data lakes, and real-time processing capabilities. The discussion extends to talent acquisition challenges and organizational models that support effective data science implementation. The article further investigates how advanced machine learning techniques are being applied across various financial domains and emphasizes the importance of aligning data initiatives with strategic business objectives. Finally, it addresses the regulatory and ethical considerations unique to financial data applications, highlighting governance frameworks that balance innovation with compliance requirements.
Keywords: Big data infrastructure, financial analytics, machine learning applications, regulatory compliance, talent development
