Integration of data from heterogeneous sources using ETL technology

Abstract

Data integration is a crucial issue in the environments of heterogeneous data sources. At present, the afore-mentioned heterogeneity is becoming widespread. Based on various data sources, if we want to gain useful information and knowledge, we must solve data integration problems in order to apply appropriate analytical methods to comprehensive and uniform data. Such activity is known as knowledge discovery from the data process. Therefore, approaches to the data integration problem are very interesting and bring us closer to the »age of information«. This paper presents an architecture which implements knowledge discovery from the data process. The solution combines ETL technology and a wrapper layer known from mediated systems. It also provides semantic integration through connection mechanism between data elements. The solution allows for integration of any data sources and implementation of analytical methods in one environment. The proposed environment is verified by applying it to data sources in the foundry industry.