Abstract

This paper explores the advancements in data mart architecture and the significant role of cloud platforms in optimizing Business Intelligence (BI) systems for global enterprises. With the increasing volume and complexity of data in today's business environment, organizations require scalable and efficient solutions for data storage, processing, and analysis. The evolution of data marts from traditional on-premise repositories to flexible, cloud-based architectures is examined, highlighting how these advancements meet the demands of modern BI systems. Cloud platforms such as AWS Redshift, Google BigQuery, and Microsoft Azure Synapse Analytics are analyzed for their contributions to enhancing BI capabilities, enabling real-time analytics, seamless integration, and on-demand scalability. Furthermore, the paper delves into the challenges of optimizing BI in cloud environments, including data governance, cost management, and integration issues. The integration of diverse data sources and the management of security and compliance requirements are identified as key concerns for global enterprises. Despite these challenges, cloud-based BI systems offer significant benefits in terms of improved decision-making, operational efficiency, and business agility. The paper concludes by discussing future trends in data mart architecture and cloud BI integration, including the role of artificial intelligence, machine learning, and enhanced data security protocols in shaping the future of global BI systems.