Evolution of Data Warehouse Architecture from Local to Cloud

Abstract

In today's era, organizations are more committed to analyzing, studying, and prioritizing data to make data-driven business decisions. Companies' critical decisions and key performance metrics revolve around understanding data. All effective decision-making begins with reliable data, and the Data Warehouse serves as the definitive source of information. The Data Warehouses have improved from single-node static tightly coupled models to dynamic separate cloud, storage, and compute models. This research paper not only studies and evaluates data warehousing architectures from traditional on-premises to the latest cloud models but also highlights the challenges of conventional systems. Importantly, it emphasizes how modern architecture provides practical, real-world solutions, thereby reassuring the audience about the effectiveness of the research. It further discussed a couple of modern architectures of leading data warehouses and recommended their powerful features. Finally, it summarizes the key components of these data warehouses' technological advancements.