Sarcouncil Journal of Multidisciplinary

Abstract: The digital transformation of data analytics has catalyzed the evolution of big data processing systems, demanding innovative solutions for real-time insights and scalable operations. As organizations face unprecedented growth in data volumes and complexity, the integration of distributed computing, stream processing, and machine learning capabilities becomes essential. Advanced architectures incorporating automated data quality frameworks, sophisticated governance mechanisms, and intelligent performance optimization strategies enable organizations to effectively manage and derive value from their expanding data assets. The implementation of these solutions, supported by container orchestration, in-memory computing, and AI-driven resource management, provides the foundation for next-generation analytics platforms that can adapt to changing business requirements while maintaining reliability and performance.