FINANCIAL DATA PROCESSING USING CLOUD-BASED DATA ANALYTICS & DATA MANAGEMENT

Abstract

In the modern financial landscape, the exponential growth of data generated by digital transactions, IoT devices, and online banking has created significant challenges for traditional data processing methods. This paper proposes a cloud-based solution for financial data processing, utilizing advanced data compression, exploratory data analysis (EDA), and cloud data management. The adoption of Optimized Row Columnar (ORC) storage format reduces storage requirements by up to 60%, while cloud platforms like AWS, GCP, and Azure provide scalable and cost-effective resources. Real-time analytics powered by AI-driven tools enable better decision-making for financial institutions. Despite the benefits, challenges related to data privacy, latency, and system integration persist, which are mitigated through hybrid cloud models and enhanced encryption techniques.