Architecting Scalable Data Engineering Pipelines for Real-Time Processing in High-Dimensional Data Ecosystems
Abstract
The exponential growth of high-dimensional data has necessitated scalable and efficient real-time data engineering pipelines. This paper explores the architecture and design of such pipelines, focusing on scalability, fault tolerance, and real-time processing capabilities. The study synthesizes prior literature, identifies key trends, and presents insights into optimal practices for managing complex data ecosystems.
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