Panoramic modeling method of multi-application system

Abstract

The invention discloses a panoramic modeling method of a multi-application system. The method comprises the following steps of: the first step: determining structure and data classification of a panoramic model of the multi-application system, (1) selecting a core model, wherein a specific application model in the core model is used as expansion of application models of other professional systems, and forming a hierarchical type panoramic model merged with each application model based on the core model; and (2) classifying the data in the panoramic model into three classes: model static data, real-time acquired data, historical and statistical data, wherein the model static data are physically integrated during panoramic modeling, the real-time acquired data, namely the process data, are not stored in the panoramic model and are integrated by data federation, and the historical data, based on the difference of the size of historical data volume, are respectively integrated by a physical integration mode and a federation integration mode; and the second step: realizing panoramic modeling based on a unified global object ID, specifically, selecting the data of the core model as the source of accurate data, and then, expanding other professional system models to present the panoramic model based on the core model.

Description

technical field [0001] The invention relates to a panorama modeling method for a multi-application system, in particular to a panorama modeling method for a multi-specialty application system in a power system. Background technique [0002] With the rapid development of enterprise informatization, more and more application systems for production, monitoring, resource management and office automation are emerging. While it is convenient for managers to use, it also brings a series of problems. First, the systems are independent of each other, with different standards and architectures, making data interaction and interoperability difficult; second, each system stores the data it needs, and the same data may be stored by multiple systems, resulting in data redundancy ; Third, due to the different requirements of each system for data type, accuracy and presentation form, the data may be inconsistent; fourth, applications or services such as data analysis and decision informati...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that data from multiple systems are directly stored in the data warehouse, and when the amount of data is too large, hardware costs and maintenance costs continue to rise

But its disadvantage is that it is not suitable for large batches of data

Moreover, data access needs to go through additional queries. For some data that needs to be accessed frequently, it consumes too much resources.

Images