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Building scalable business intelligence systems in the cloud: A technical approach
University of North America, Virginia, United States of America.
Review
International Journal of Science and Research Archive, 2021, 02(01), 212-215.
Article DOI: 10.30574/ijsra.2021.2.1.0047
Publication history:
Received on 03 February 2021; revised on 17 April 2021; accepted on 19 April 2021
Abstract:
Building scalable Business Intelligence (BI) systems in the cloud has become a crucial strategy for modern enterprises aiming to harness the power of data analytics for informed decision-making. Cloud-based BI systems offer unprecedented scalability, flexibility, and cost-effectiveness compared to traditional on-premises solutions. This paper delves into the technical approach to designing and implementing scalable BI systems in the cloud. It covers essential aspects such as cloud architecture, data integration, security considerations, and real-time analytics. By leveraging services from leading cloud providers like AWS, Azure, and Google Cloud Platform, organizations can address the challenges of growing data volumes and ensure seamless scalability. The paper also examines best practices for data pipeline optimization, storage management, and the integration of advanced technologies like machine learning and artificial intelligence. Furthermore, the discussion highlights how a well-architected BI system can align with organizational goals, driving efficiency and innovation. This technical guide aims to provide IT professionals and business stakeholders with actionable insights into adopting and optimizing BI systems in the cloud.
Keywords:
Business Intelligence; Cloud Computing, Scalability; Data Analytics; Aws; Azure; Google Cloud Platform; Data Integration; Real-Time Analytics; Machine Learning
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Copyright information:
Copyright © 2021 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
