сховище даних

Архітектура багаторівневої системи управління енергоефективністю регіону

The list of problems that can be solved by multilevel system of energy efficiency of the region were determined. Requirements for the implementation of each system component were formulated. It was shown that the technological process control’s components should provide processing of intensive data streams in real time. Also components have to satisfy limitations on size, power consumption and cost.

The data warehouse construction for decision support system for designing distributed energy systems

This paper discusses the problems that arise when working with disparate data sources using database. The model of data warehouse is presented as way of integrating and processing data from disparate sources while creating a decision support system for the design of distributed energy systems.

Aspects manifestation of uncertainty in the process of developing decision support systems

This article describes the classification and approaches to the construction of DSS that take into account various aspects of the uncertainty of the development of DSS. Features of the classification were proposed and described. Generalized classification of DSS was improved. The analysis of the types of architecture, architecture reviewed information resource decision support systems, based on the principles of building a data warehouse.

Консолідований інформаційний ресурс економічних показників регіону

In this article information from the management objects regarding the data consolidation processes obtained from both internal and external sources is collected and analyzed. On this basis data warehouse is built. Integration and analysis means of diverse input data of the region economic sphere are developed.

Ontology data cleansing

This article describes the steps to clear data in the DSS. The ontology concepts of clear data were proposed and described. The analysis of methods and data cleansing technology were carried out at every stage of the process, taking into account its features. Built The ontology of data cleaning techniques for methodological systematization of functional elements in the implementation model of DSS was built.