Customized and efficient management of compute, storage, and communication in Big Data Processing and its optimization

There are specific challenges like handling of variety datasets, velocity, and largest, high dimensional datasets to be handled efficiently in big data processing and its optimization. In this, three crucial aspects considered such as computing, computation storage, and communication in big data optimization. For achieving accurate and timely data assessment and analysis, these three aspects are focused on insights for rest to be assured for future endeavors. The strategies used on computing aspect enable to provide fast data access, effective allocation of resources, and parallel processing. The approaches considered are distributed frameworks, in-memory systems, lazy evaluations, partitioning, and selective algorithms. The second aspect is computation storage which requires hardware, software tools, Orchestration tools, Analytics tools, and data management tools for faster access, efficient data movements, enhanced scalability, and effective security. The third aspect of big data optimization is communication in which the approaches considered related to infrastructure, serialization, protocols, and notification/alerting systems to experience less overhead, proactive issue detection, and effective data exchange. This integrated aspects leads to efficient informed decision making based on insights and significant analysis. The customized framework on compute, communication services in big data optimization results accuracy, scalability, processing efficiency, and visualization analysis in better manner against existing approaches.