Cloud and Data Transformation in Banking: Managing Middle and Back Office Operations Using Snowflake and Databricks

Abstract

To improve their data transformation procedures used in their back-office and middle-office activities, leading financial institutions are slowly but surely adopting cloud computing. With a focus on cloud-based technologies and platforms like Snowflake and Databricks, this article aims to explore the program management approaches used in transformation initiatives. This study focuses on the complexities of handling large transitions. The complications include data migration, system integration, and regulatory compliance issues. It also underlines how cloud-native solutions improve operational efficiency, scalability, and data accessibility. Case studies from the banking industry show that managing cloud migration requires careful preparation, cross-departmental coordination, and adaptable techniques. The essay focuses on the key findings and proposes an approach that banks and other financial institutions may use to improve their data architecture and optimize cloud operations.