In this study, we delve into the realm of efficient Big Data Engineering and Extract, Transform, Load (ETL) processes within the healthcare sector, leveraging the robust foundation provided by the MIMIC-III Clinical D...In this study, we delve into the realm of efficient Big Data Engineering and Extract, Transform, Load (ETL) processes within the healthcare sector, leveraging the robust foundation provided by the MIMIC-III Clinical Database. Our investigation entails a comprehensive exploration of various methodologies aimed at enhancing the efficiency of ETL processes, with a primary emphasis on optimizing time and resource utilization. Through meticulous experimentation utilizing a representative dataset, we shed light on the advantages associated with the incorporation of PySpark and Docker containerized applications. Our research illuminates significant advancements in time efficiency, process streamlining, and resource optimization attained through the utilization of PySpark for distributed computing within Big Data Engineering workflows. Additionally, we underscore the strategic integration of Docker containers, delineating their pivotal role in augmenting scalability and reproducibility within the ETL pipeline. This paper encapsulates the pivotal insights gleaned from our experimental journey, accentuating the practical implications and benefits entailed in the adoption of PySpark and Docker. By streamlining Big Data Engineering and ETL processes in the context of clinical big data, our study contributes to the ongoing discourse on optimizing data processing efficiency in healthcare applications. The source code is available on request.展开更多
This paper analyzes the advantages of legal digital currencies and explores their impact on bank big data practices.By combining bank big data collection and processing,it clarifies that legal digital currencies can e...This paper analyzes the advantages of legal digital currencies and explores their impact on bank big data practices.By combining bank big data collection and processing,it clarifies that legal digital currencies can enhance the efficiency of bank data processing,enrich data types,and strengthen data analysis and application capabilities.In response to future development needs,it is necessary to strengthen data collection management,enhance data processing capabilities,innovate big data application models,and provide references for bank big data practices,promoting the transformation and upgrading of the banking industry in the context of legal digital currencies.展开更多
文摘In this study, we delve into the realm of efficient Big Data Engineering and Extract, Transform, Load (ETL) processes within the healthcare sector, leveraging the robust foundation provided by the MIMIC-III Clinical Database. Our investigation entails a comprehensive exploration of various methodologies aimed at enhancing the efficiency of ETL processes, with a primary emphasis on optimizing time and resource utilization. Through meticulous experimentation utilizing a representative dataset, we shed light on the advantages associated with the incorporation of PySpark and Docker containerized applications. Our research illuminates significant advancements in time efficiency, process streamlining, and resource optimization attained through the utilization of PySpark for distributed computing within Big Data Engineering workflows. Additionally, we underscore the strategic integration of Docker containers, delineating their pivotal role in augmenting scalability and reproducibility within the ETL pipeline. This paper encapsulates the pivotal insights gleaned from our experimental journey, accentuating the practical implications and benefits entailed in the adoption of PySpark and Docker. By streamlining Big Data Engineering and ETL processes in the context of clinical big data, our study contributes to the ongoing discourse on optimizing data processing efficiency in healthcare applications. The source code is available on request.
文摘This paper analyzes the advantages of legal digital currencies and explores their impact on bank big data practices.By combining bank big data collection and processing,it clarifies that legal digital currencies can enhance the efficiency of bank data processing,enrich data types,and strengthen data analysis and application capabilities.In response to future development needs,it is necessary to strengthen data collection management,enhance data processing capabilities,innovate big data application models,and provide references for bank big data practices,promoting the transformation and upgrading of the banking industry in the context of legal digital currencies.
