Zero ETL for Cloud-Native Applications on AWS: A Paradigm Shift in Data Processing and Quality Assurance

Abstract—the advent of cloud-native applications has

revolutionized the way data is processed, stored, and analyzed.

Traditional Extract, Transform, Load (ETL) processes, while

effective, often introduce latency, complexity, and scalability

challenges. This paper explores the concept of Zero ETL, a

paradigm shift in data processing that leverages the inherent

capabilities of cloud-native platforms like Amazon Web Services

(AWS) to eliminate the need for traditional ETL pipelines. We

delve into the architectural principles, benefits, and challenges

of Zero ETL, with a focus on its implications for data quality

assurance. Through a combination of theoretical analysis, case

studies, and empirical data, we demonstrate how Zero ETL can

enhance data processing efficiency, reduce operational

overhead, and improve data quality in cloud-native

environments. The paper concludes with a discussion on future

research directions and practical considerations for adopting

Zero ETL in enterprise settings.

Keywords—AWS, Cloud-Native Applications, Cost Efficiency,

Data Governance, Data Processing, Quality Assurance, Real-

Time Analytics, Scalability, Server less Computing, Zero ETL.