Overview of Data Warehouse architecture, Big Data and Green computing

Abstract

Enterprise today heavily invests in big data, data warehouses, and green computing to measure performance and make intelligent decisions. By enabling data warehouse architecture, enterprises can store structural and nonstructural data in defined backend systems and transform amounts of data to perform various analyses and make business decisions that put companies on top of their competitors. Data is increasing daily, and businesses want to use all their data to perform advanced business analytics and machine learning and distribute data to their backend algorithms to evaluate and make decisions faster. However, the carbon footprints and global warming have alarmed these organizations to move towards green computing for a better future. Green computing focuses on designing energy-efficient systems, optimizing resource utilization, and reducing the CO2 emissions of data centers and IT infrastructure. This paper reviews how data warehouse architecture, big data, and green computing relate and addresses the challenges and opportunities in achieving sustainable and scalable data management solutions. By integrating energy-efficient practices into data warehouses and big data systems, organizations can make a huge difference globally and set an example for other industries to follow the green computing path. This paper helps to understand the new paradigm of big data and green computing, which helps achieve the best performance, reduce environmental impacts, and achieve the best standards.