Published Paper Details:

Abstract The rise of containerization technology has significantly transformed data analytics in various sectors, including financial services. This research paper explores the application and impact of containerized data analytics solutions within on-premise financial services environments. Containerization, which involves encapsulating applications and their dependencies into portable containers, offers a scalable and flexible approach to managing complex data analytics tasks. In on-premise financial services, where data security, regulatory compliance, and system integration are paramount, containerized solutions present a compelling alternative to traditional data processing methods. This study investigates the benefits and challenges associated with implementing containerized data analytics solutions in on-premise settings. Key advantages include enhanced scalability, as containers allow for dynamic allocation of resources based on workload demands, and improved efficiency through isolated and consistent environments that streamline application deployment. Additionally, containerization supports better resource utilization and faster development cycles, leading to more agile and responsive data analytics capabilities. However, the implementation of containerized solutions in on-premise financial services also presents several challenges. These include the need for specialized knowledge to manage container orchestration and integration with existing legacy systems. Furthermore, ensuring data security and compliance with stringent financial regulations requires careful planning and robust security measures. The paper discusses strategies for overcoming these challenges, including the adoption of container orchestration platforms like Kubernetes, and integrating containerized solutions with existing security protocols and compliance frameworks. The research employs a case study approach, analyzing real-world implementations of containerized data analytics in on-premise financial institutions. Findings reveal that, while containerization offers substantial improvements in agility and efficiency, successful deployment necessitates addressing specific challenges related to integration and security.