Real-Time Data Engineering in the Financial Sector

Abstract

With an emphasis on present trends, underlying difficulties, and potential future developments, this study offers a thorough analysis of the developing role of big data analytics in the financial services sector. In order to comprehend how big data analytics is changing financial services, including the insurance, financial services, and investment industries, the goal is to compile the body of current research and best practices. Data engineering breakthroughs are causing a significant upheaval in the financial services sector. This study looks at how data engineering greatly improves consumer experiences and operational efficiency in a variety of fields, including as algorithmic trading, risk management, customized banking, and fraud detection. The use of cutting-edge data engineering techniques is propelling the financial services industry's fast development. Financial organizations may increase productivity and cultivate stronger client connections by using data to optimize operations and improve customer experiences. In addition, we provide a thorough data engineering framework designed specifically for financial institutions, combining cutting-edge tools and techniques to tackle problems unique to the sector. By providing a plan for more efficient data integration, administration, and analysis, this framework supports financial innovation and regulatory compliance. We also examine the potential and challenges of using these data engineering techniques, highlighting the vital need of strong data governance and ethical issues in the financial sector.