A Comparative Study of Apache Flink and Spark in Real-Time Financial Data Analytics

الملخص

With the rapid development of banking and financial technology, smart banking applications are generating ever-increasing data, making big data analysis in the banking sector no longer a luxury but a necessity for operating effectively in this data-driven digital environment. Data analytics in the banking sector can help generate in-depth insights into customer behavior, enhancing their ability to provide more personalized and proactive customer service, improving customer experience, and strengthening trust between them and their banking institutions. This study aims to shed light on the use of Internet of Things (IoT) technology in the banking sector and explore appropriate methods for analyzing the resulting data by it. In this context, the study compared the Apache Flink and Apache Spark platforms to determine the most appropriate solution for real-time data analysis tasks. This study contributes to bridging the existing gap in helping banking institutions choose the appropriate data analysis platform according to their needs. This comprehensive systematic review constitutes the basic methodology used by the author to investigate issues related to the integration of IoT technologies and data analytics within the emerging banking industry.