Architecting resilient data pipelines: A framework for enterprise analytics in cloud environments
Year: 2025
Type: article
Abstract: The proliferation of data in modern enterprises necessitates robust pipeline architectures capable of handling massive volumes while maintaining performance and compliance. This article presents a comprehensive framework for designing scalable data pipelines that effectively support enterprise analytics initiatives. The framework addresses critical aspects including modular orchestration components, fault-tolerance mechanisms, governance integration, and migration optimization techniques. Particular attention is given to the implementation of tools such as Apache Airflow and AWS Glue for workflow management, alongside strategies for minimizing downtime during transitions to cloud data warehouses. Through the adoption of Infrastructure as Code and containerized workflows, organizations can achieve significant improvements in pipeline efficiency and adaptability. The proposed architecture enables enterprises to maintain data quality and regulatory compliance while delivering actionable insights at scale, ultimately providing a foundation for data-driven decision making across the organization.
Author: Ritesh Kumar Sinha
Institution: Amazon (United States)
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4411255495