超级计算技术推动企业信息系统和数字经济发展

O. V. Loginovsky, A. Shestakov, A. Shinkarev
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引用次数: 4

摘要

本文对目前使用的企业信息系统开发方法进行了分析。预先决定信息技术议程的主要趋势之一是关注使用超级计算技术对大量数据进行并行计算。本文考虑了构建企业信息系统和避免单体体系结构的普遍转向分布式模式的结果。重点放在企业信息系统的可靠性、可伸缩性和可维护性等基本特征的重要性上。这篇文章证明了机器学习在有效的大数据分析和商业竞争优势背景下的重要性,这对于保持市场领先地位以及在全球不稳定和经济数字化的条件下生存至关重要。将存储企业信息系统的当前状态转换为存储事件流中所有更改的完整日志和历史记录,作为实现数据流线性化的工具,用于后续并行计算。工程和分析学科交叉领域的专家正在形成一种新的观点,他们将能够有效地开发可扩展的系统和算法,用于数据处理,并将其结果集成到公司业务流程中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Supercomputing Technologies as Drive for Development of Enterprise Information Systems and Digital Economy
The article presents an analysis of approaches to the development of enterprise information systems that are in use today. One of the major trends that predetermines the agenda of information technology is the focus on parallel computing of large volumes of data using supercomputing technologies. The article considers the resulting ubiquitous move to distributed patterns of building enterprise information systems and avoiding monolithic architectures. The emphasis is placed on the importance of such fundamental characteristics of enterprise information systems as reliability, scalability, and maintainability. The article justifies the importance of machine learning in the context of effective big data analysis and competitive gain for business, vital for both maintaining a leading position in the market and surviving in conditions of global instability and digitalization of economy. Transition from storing the current state of a enterprise information system to storing a full log and history of all changes in the event stream is proposed as an instrument of achieving linearization of the data stream for subsequent parallel computing. There is a new view that is being shaped of specialists at the intersection of engineering and analytical disciplines, who would be able to effectively develop scalable systems and algorithms for data processing and integration of its results into company business processes.
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