
ABOUT THE GENERAL CONCEPT OF THE UNIVERSAL STORAGE SYSTEM AND PRACTICE-ORIENTED DATA PROCESSING
Author(s) -
Lada Rudikova
Publication year - 2017
Publication title -
sistemnyj analiz i prikladnaâ informatika
Language(s) - English
Resource type - Journals
eISSN - 2414-0481
pISSN - 2309-4923
DOI - 10.21122/2309-4923-2017-2-12-19
Subject(s) - data warehouse , computer science , computer data storage , information repository , database , interface (matter) , data processing , process (computing) , data element , data migration , data mining , data science , world wide web , metadata , operating system , bubble , maximum bubble pressure method
Approaches evolution and concept of data accumulation in warehouse and subsequent Data Mining use is perspective due to the fact that, Belarusian segment of the same IT-developments is organizing. The article describes the general concept for creation a system of storage and practice-oriented data analysis, based on the data warehousing technology. The main aspect in universal system design on storage layer and working with data is approach uses extended data warehouse, based on universal platform of stored data, which grants access to storage and subsequent data analysis different structure and subject domains have compound’s points (nodes) and extended functional with data structure choice option for data storage and subsequent intrasystem integration. Describe the universal system general architecture of storage and analysis practice-oriented data, structural elements. Main components of universal system for storage and processing practice-oriented data are: online data sources, ETL-process, data warehouse, subsystem of analysis, users. An important place in the system is analytical processing of data, information search, document’s storage and providing a software interface for accessing the functionality of the system from the outside. An universal system based on describing concept will allow collection information of different subject domains, get analytical summaries, do data processing and apply appropriate Data Mining methods and algorithms.