Heterogeneous Data Integration Architecture-Challenging Integration Issues

Michal Chromiak, Marcin Grabowiecki

Abstract


As of today, most of the data processing systems have to deal with a large amount of data originated from numerous sources. Data sources almost always differ regarding its purpose of existence. Thus model, data processing engine and technology differ intensely. Due to current trend for systems fusion there is a growing demand for data to be present in a common way regardless of its legacy. Many systems have been devised as a response to such integration needs. However, the present data integration systems mostly are dedicated solutions that bring constraints and issues when considered in general. In this paper we will focus on the present solutions for data integration, their flaws originating from their architecture or design concepts and present an abstract and general approach that could be introduced as an response to existing issues. The system integration is considered out of scope for this paper, we will focus particularly on efficient data integration.

Keywords


grid integration model, heterogeneous integration, distributed architecture, data integration, big data, distributed transaction, warehouse, ETL, OLAP

Full Text:

PDF


DOI: http://dx.doi.org/10.17951/ai.2015.15.1.7-11
Data publikacji: 2015-01-01 00:00:00
Data złożenia artykułu: 2016-04-28 09:13:05


Statistics

Total abstract view - 159
Downloads (from 2020-06-17) - PDF - 0

Indicators



Refbacks

  • There are currently no refbacks.


Copyright (c) 2015 Annales UMCS Sectio AI Informatica

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.