针对伺服阀生产过程中存在的设备种类繁多、不同供应商设备之间无法交换数据、数据集成工作复杂困难的问题,提出基于OPC UA (Object Linking and Embedding for Process Control Unified Architecture)和ETL (Extract-Transform-Load)...针对伺服阀生产过程中存在的设备种类繁多、不同供应商设备之间无法交换数据、数据集成工作复杂困难的问题,提出基于OPC UA (Object Linking and Embedding for Process Control Unified Architecture)和ETL (Extract-Transform-Load)的综合解决方案。该方案使用OPC UA作为通信协议完成设备之间的高效通信,利用ETL技术设计并实现了伺服阀综合应用系统。样机试验验证了方案的有效性。该方案实现了产线信息化过程中的设备互操作能力,是确保伺服阀质量可靠性和性能一致性的关键基础技术。展开更多
The extraction,transformation,and loading(ETL)process is a crucial and intricate area of study that lies deep within the broad field of data warehousing.This specific,yet crucial,aspect of data management fills the kn...The extraction,transformation,and loading(ETL)process is a crucial and intricate area of study that lies deep within the broad field of data warehousing.This specific,yet crucial,aspect of data management fills the knowledge gap between unprocessed data and useful insights.Starting with basic information unique to this complex field,this study thoroughly examines the many issues that practitioners encounter.These issues include the complexities of ETL procedures,the rigorous pursuit of data quality,and the increasing amounts and variety of data sources present in the modern data environment.The study examines ETL methods,resources,and the crucial standards that guide their assessment in the midst of this investigation.These components form the foundation of data warehousing and act as a safety net to guarantee the dependability,accuracy,and usefulness of data assets.This publication takes on the function of a useful guide for academics,professionals,and students,despite the fact that it does not give empirical data.It gives students a thorough grasp of the ETL paradigm in the context of data warehousing and equips them with the necessary skills to negotiate the complex world of data management.This program equips people to lead effective data warehousing initiatives,promoting a culture of informed decision-making and data-driven excellence in a world where data-driven decision-making is becoming more and more important.展开更多
数据抽取、转换和装载(Extraction,Transformation and Loading,简称ETL)是数据仓库化的关键环节,对数据仓库数据质量有着至关重要的影响。随着信息化的发展,ETL已经成为当前较活跃的研究领域之一,但是ETL理论和技术的发展还不成熟。针...数据抽取、转换和装载(Extraction,Transformation and Loading,简称ETL)是数据仓库化的关键环节,对数据仓库数据质量有着至关重要的影响。随着信息化的发展,ETL已经成为当前较活跃的研究领域之一,但是ETL理论和技术的发展还不成熟。针对当前ETL研究中存在的一些问题和需要考虑的各种因素,从ETL各个阶段存在的主要问题出发,列举了各种研究方法及研究成果,并进行了分析。最后,总结并提出了ETL的未来研究方向和今后工作的建议。展开更多
文摘针对伺服阀生产过程中存在的设备种类繁多、不同供应商设备之间无法交换数据、数据集成工作复杂困难的问题,提出基于OPC UA (Object Linking and Embedding for Process Control Unified Architecture)和ETL (Extract-Transform-Load)的综合解决方案。该方案使用OPC UA作为通信协议完成设备之间的高效通信,利用ETL技术设计并实现了伺服阀综合应用系统。样机试验验证了方案的有效性。该方案实现了产线信息化过程中的设备互操作能力,是确保伺服阀质量可靠性和性能一致性的关键基础技术。
文摘The extraction,transformation,and loading(ETL)process is a crucial and intricate area of study that lies deep within the broad field of data warehousing.This specific,yet crucial,aspect of data management fills the knowledge gap between unprocessed data and useful insights.Starting with basic information unique to this complex field,this study thoroughly examines the many issues that practitioners encounter.These issues include the complexities of ETL procedures,the rigorous pursuit of data quality,and the increasing amounts and variety of data sources present in the modern data environment.The study examines ETL methods,resources,and the crucial standards that guide their assessment in the midst of this investigation.These components form the foundation of data warehousing and act as a safety net to guarantee the dependability,accuracy,and usefulness of data assets.This publication takes on the function of a useful guide for academics,professionals,and students,despite the fact that it does not give empirical data.It gives students a thorough grasp of the ETL paradigm in the context of data warehousing and equips them with the necessary skills to negotiate the complex world of data management.This program equips people to lead effective data warehousing initiatives,promoting a culture of informed decision-making and data-driven excellence in a world where data-driven decision-making is becoming more and more important.
文摘数据抽取、转换和装载(Extraction,Transformation and Loading,简称ETL)是数据仓库化的关键环节,对数据仓库数据质量有着至关重要的影响。随着信息化的发展,ETL已经成为当前较活跃的研究领域之一,但是ETL理论和技术的发展还不成熟。针对当前ETL研究中存在的一些问题和需要考虑的各种因素,从ETL各个阶段存在的主要问题出发,列举了各种研究方法及研究成果,并进行了分析。最后,总结并提出了ETL的未来研究方向和今后工作的建议。
