Microservices-Based Financial Data Aggregation for Enterprise Analytics: Design, Scalability, and Case Study Using Spring Boot

The rapid growth of enterprise data ecosystems, particularly in the financial domain, has created a strong need for scalable, reliable, and efficient data aggregation solutions. This research presents a microservices-based architecture for financial data aggregation designed to support enterprise analytics platforms. Leveraging the Spring Boot framework, the proposed system decomposes complex data processing workflows into independently deployable and loosely coupled services, enabling enhanced scalability, flexibility, and fault isolation. The study emphasizes key design principles such as service orchestration, asynchronous communication, and API-driven integration to efficiently handle high-volume and high-velocity financial transactions. Furthermore, the framework incorporates resilience patterns, including circuit breakers and load balancing, to ensure system reliability and high availability. A case study based on the Y&L Consulting financial data aggregation platform is used to demonstrate the practica