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Abstract
The rapid evolution of technology and the exponential growth of data have transformed numerous domains, allowing organizations. Modern products embedded with sensors and intelligent chips can track usage, system load, and environmental conditions, while emerging technologies enable early detection of component degradation and potential failures. Although big data has reshaped industries, its sheer volume, velocity, and complexity present significant challenges for maintaining reliable and resilient analytics pipelines, with optimization techniques playing a crucial role in strengthening system robustness. Data analytics has notably revolutionized maintenance practices, particularly predictive maintenance, which leverages machine learning, statistical modeling, and artificial intelligence to anticipate equipment failures. Likewise, fields such as reliability engineering, safety analytics, cybersecurity, and autonomous systems are increasingly applying machine learning to enhance performance and manage risks. Big data also underpins advancements in cloud computing, smart grids, and renewable energy, supporting operational efficiency, accurate forecasting, and informed decision-making despite inherent uncertainties.Complex sectors like neuroscience and interbank operations face additional challenges due to diverse data modalities, evolving technologies, and systemic inefficiencies, which hinder standardization, reproducibility, and operational accuracy. This survey highlights the impact of emerging data-driven approaches across these domains, demonstrating their potential to enhance reliability, security, and intelligence in practical applications. By mapping the evolving analytics landscape, this work provides a comprehensive overview of past, present, and future trends in data-centric technologies, offering valuable insights for researchers and practitioners developing robust, intelligent, and scalable systems.
Key Words: Data Analytics, Machine Learning, Predictive Maintenance, Reliability Engineering, Big Data, Optimization Techniques, System Resilience, Fault Detection, Cyber-Physical Systems, Intelligent Decision-Making.
