Information integration is the merging of information from different data sets (data sources) with usually different data structures into a common, uniform data structure with the aim of providing a consistent global view of all data sources. Redundant data sources can be used for verification. The merging of intensional redundant sources leads to higher coverage and the completion of data sets with extensional redundancy of sources to a higher density.
In particular, heterogeneous sources should be brought together as completely and efficiently as possible to form a structured unit that can be used more effectively than would be possible with direct access to the individual sources. Information integration is particularly necessary where several mature systems are to be linked together, for example when merging companies, workflows and applications or when searching for information on the Internet.
Smart Commerce combines popular methods for extracting data from heterogeneous sources, transforming it and loading it into a unified system.
For this purpose, automated query interfaces are used to query the data in real time. This allows the data to be queried directly from the heterogeneous sources, which provides an advantage in the timeliness of the data. Data isolation artifacts are avoided and integrated into the data structure.
The integration of heterogeneous information from different sources concerns both the integration of concrete data and the structures (schemata) in which it exists. First, the local schemas are integrated (schema integration), for which (partially) automatic methods are also used (schema matching), and then data fusion and duplicate recognition methods necessary for data integration are implemented.