Open AccessABOUT DATA MODELING SUBJECT DOMAINS PRACTICE-ORIENTED DIRECTION FOR UNIVERSAL SYSTEM OF STORAGE AND PROCESSING DATA
Author(s) -
Lada Rudikova,
Е. В. Жавнерко
Publication year - 2017
Publication title -
sistemnyj analiz i prikladnaâ informatika
Language(s) - English
Resource type - Journals
eISSN - 2414-0481
pISSN - 2309-4923
DOI - 10.21122/2309-4923-2017-3-4-12
Subject(s) - data warehouse , computer science , data model (gis) , data element , data modeling , computer data storage , data type , storage model , data virtualization , flexibility (engineering) , data mining , database , data science , metadata , artificial intelligence , cloud computing , programming language , statistics , mathematics , virtualization , operating system
This article describes data modeling for practice-oriented subject domains they are basis of general data model for data warehouse creation. Describes short subject domains characteristic relationship to different types of any human activities at the current time. Offered appropriate data models, considered relationship between them as data processing and data warehouse creation, which can be built on information data storage technology and which has some characteristics as extensible complex subject domain, data integration, which get from any data sources, data time invariance with required temporal marks, relatively high data stability, search necessary compromises in data redundancy, system blocks modularity, flexibility and extensibility of architecture, high requirements to data storage security. It’s proposed general approach of data collection and data storage, appropriate data models, in the future, will integrate in one database scheme and create generalized scheme of data warehouse as type «constellation of facts». For getting of data models applies structural methodology and consider general principles of conceptual design. Using complex system, which can work with some information sources and represent data in convenient view for users will in-demand for analysis data selected subject domains and determination of possible relationships.