DATA INGESTION PATTERNS IN BIG DATA SYSTEMS: AN ANALYSIS OF METHODS, ARCHITECTURES, AND IMPLEMENTATION STRATEGIES

This article comprehensively analyzes data ingestion patterns in modern big data systems, examining their methods, architectures, and implementation strategies.The article explores the evolution of data management systems and their transformation from basic batch processing to sophisticated distributed architectures.It shows various data ingestion patterns, including batch processing, real-time processing, micro-batch architecture, and event-driven systems, while analyzing their effectiveness across different industry verticals.The article addresses critical aspects such as data quality management, scalability design, fault tolerance, monitoring, and security considerations in implementing these patterns.The article provides insights into