基于OLAP的多维数据分布监控

Yifan Mao, Shasha Huang, Shuo Cui, Haifeng Wang, Junyan Zhang, Wenhao Ding
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摘要

随着互联网的飞速发展,社会逐渐进入信息化时代,企业中的各种数据已经成为所有企业最重要的战略核心资源。企业的经营和决策都需要大量的数据分析。目前,很多企业对数据资产分布的监控不够重视。此外,财务管理、ERP系统等内部各系统相对独立。每个系统都有自己的数据组织标准,很难对数据进行统一管理。这也直接导致了企业管理者对数据资产分布的片面和主观问题。随着各企业数据中心的建设,各系统的数据通过数据集成技术汇聚到中心。因此,各企业都需要围绕数据链路构建多维度的数据分布监控模型,全面监控企业全网各种数据分布的状态,提升数据服务能力和共享能力,提升企业运营能力。本文利用OLAP技术构建了电力企业数据集成过程中数据链的多维数据分布监控模型。本文首先选取了多维数据中需要监控的维度和指标,然后利用在线分析处理技术构建了多维数据的概念模型、逻辑模型和物理模型。最后,对基于B/S结构的OLAP系统体系结构进行了实例分析。通过分析数据链的各个维度,如系统类型、位置分布、时间分布等,可以掌握企业整体的数据分布情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi dimensional data distribution monitoring based on OLAP
With the rapid development of the Internet, society is gradually entering the information age, and various data in enterprises have become the most important strategic core resources of all enterprises. The operation and decision-making of enterprises all require a large amount of data analysis. Nowadays, many companies do not pay enough attention to the monitoring of data asset distribution. In addition, various internal systems such as financial management and ERP systems are relatively independent. Each system has its own data organization standard, which makes it difficult to conduct a unified management of data. This also directly leads to the one-sided and subjective problem of enterprise managers' distribution of data assets. With the construction of the data center of each enterprise, the data of each system is aggregated to the center through data integration technology. Therefore, all enterprises need to build a multi-dimensional data distribution monitoring model around data links to comprehensively monitor the status of various data distributions across the company's entire network, and improve data service capabilities and sharing capabilities as well as the company's operational capabilities. This article uses OLAP technology to construct a multi-dimensional data distribution monitoring model for the data link in the process of power enterprise data integration. This article first selects the dimensions and metrics that need to be monitored in the multidimensional data, and then constructs the conceptual model, logical model and physical model of the multidimensional data using on line analytical processing technology. Finally, an example analysis of OLAP system architecture based on B/S structure is realized. The overall data distribution of the enterprise can be grasped by analyzing the various dimensions of the data link, such as System type, location distribution, and time.
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