Cloud Data Stack Scalability: A Case Study on Migrating from Legacy Systems
Abstract
The migration of data systems to cloud-based architectures has become increasingly prevalent as organizations seek scalability, flexibility, and cost-efficiency. This paper presents a case study on the migration from legacy systems to a cloud data stack, focusing on scalability considerations and challenges encountered throughout the process. The abstract begins by highlighting the growing importance of scalability in modern data architectures, driven by the exponential growth of data volumes and the need for elastic and responsive infrastructure. It underscores the limitations of legacy systems in meeting the scalability demands of today's data-intensive applications. The paper navigates through the conceptual framework of a cloud data stack, elucidating its components and advantages in facilitating scalability, including cloud storage, data warehouses, and compute resources.
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