• Korlakunta gowthami

In data exchange, data structured under one schema (Source schema) must be structured and translated into an instance of a different schema (Target schema). It is the process of generating an instance of a target schema from an instance of a source schema such that source data is reflected in the target instance. The prevailing approach for this process is based on schema mappings high level relations between source and target areas. Schema mapping involves the discovery of a query or set of queries that transform the source data into the new structure. Data exchange solely based on the schema level information limits the ability to express semantics in data exchange. In this schema level mappings not only may result in entity fragmentation, but also leads to ambiguous data exchange scenarios. In proposed system, Scalable Entity Preserving Data Exchange a hybrid method based on data and schema mapping. The mapping method out forms other methods in terms of quality and scalability of data exchange. And the source and target can be represented through schema and data level information big knowledge bases.

scalable,dataexchange.

"automatic entity mapping for scalable data exchange", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 6, page no.635-639, June-2018, Available :http://www.jetir.org/papers/JETIR1806334.pdf

"automatic entity mapping for scalable data exchange", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 6, page no. pp635-639, June-2018, Available at : http://www.jetir.org/papers/JETIR1806334.pdf