Leveraging Snowflake for Scalable Financial Data Warehousing

Purpose: The study discusses the increasing challenges faced by financial services due to fast-growing transaction, regulatory, and client data, and the need for more flexible, scalable, and affordable data management systems. It examines the potential of Snowflake, a cloud-based data warehousing platform, to address these issues through its multi-cluster shared data architecture Methodology: The paper analyzes Snowflake's architecture, focusing on its ability to decouple storage from compute, allowing organizations to scale resources as needed. Case studies of financial institutions implementing Snowflake are also examined to highlight key outcomes, benefits, and challenges. Findings: Snowflake helps financial institutions handle massive transactional and historical data for real-time analytics, better decision-making, and strong regulatory compliance. Case studies show the platform handles massive data sets efficiently and cost-effectively Recommendations: Snowflake-using financial institutions are advised on cloud-based financial data management research and strategy. For successful implementation, it addresses data transfer, regulatory compliance, cloud cost management, and user engagement issues.