Year: 2024
Type: article
Abstract: As enterprises battle exponential data expansion and increasingly complicated analytics requirements, the demand for scalable, efficient data infrastructures has never been more vital. This extensive technical article gives a complete approach to developing and implementing a modern data lake architecture using AWS cloud services. A production-grade solution leverages Amazon S3 for persistent storage, AWS Glue for robust ETL processing, and Amazon Athena for cost-effective querying capabilities. The design integrates fundamental features of data governance, security, and operational excellence while solving typical difficulties in enterprise data management. A deep investigation of component layers-from data ingestion to storage organization, processing pipelines, and query optimization provides practical insights for developing a scalable data platform. The article covers essential concerns for data architects and engineers, including storage optimization tactics, data quality frameworks, monitoring systems, and cost control procedures. Real-world implementation patterns and case studies highlight how firms can migrate from classic data warehousing systems to modern, cloud-native data architectures that enable advanced analytics and machine learning projects.
Author: Venkata Raghavendra Vutti -
Institution: University of Central Missouri
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4405635913