الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Data warehousing is one of the more powerful tools available to support a business enterprise, it provides a multidimensional view of data in an intuitive model designed to match the types of queries posed by analysts and decision makers. Schema mapping plays a key role in many different applications, such as schema integration, data integration, data warehousing, data transformation, E-commerce, peer-to-peer data management, ontology matching and integration, semantic Web. In order to analyze e-commerce and make reasonable business plans, a company’s local data is not sufficient. Decision making must also be based on information from suppliers, partners and competitors. This external data can be obtained from the Web in many cases Such XML, but must be integrated with the company’s own data, for example, in a data warehouse. To this end, Web data has to be mapped to the star schema of the warehouse.
In this thesis we propose a semiautomatic approach to support this transformation process. Our approach is based on the use an XML Schema representation of Web data and the existing warehouse schema. Based on this common view we can compare source and target schema to identify correspondences. We show how the correspondences guide the transformation to be accomplished automatically. We also explain the meaning of Data cleaning and apply it on XML web data to restructuring web data according to DW (Data Warehouse) schema, which are the core of the transformation process using XSLT (Extensible Stylesheet Language Transformations) and XPATH (XML Path Language).
Building a data warehouse for XML documents has become a very important issue, when considering the continual growth of representing different kinds of data as XML documents. This is one of the reasons why researchers became interested in studying ways to optimize processing of XML documents and to obtain a better data warehouse to store optimized information for future reference.