In the data warehousing approach to the integration of data from multiple information sources, selected information is extracted in advance and stored in a repository. A data warehouse (DW) can therefore be seen as a set of materialized views deened over the sources. When a query is posed, it is evaluated locally, using the materialized views, without access-ing the original information sources...

With the proliferation of XML-based data sources available across the Internet, it is increasingly important to provide users with a data warehouse of XML data sources to facilitate decision-making processes. Due to the extremely large amount of XML data available on web, unguided warehousing of XML data turns out to be highly costly and usually cannot well accommodate the users’ needs in XML d...

A Data warehouse has its own set of challenges for security. Organizational data warehouse are often very large systems. Once we have extracted and loaded the data from heterogeneous sources we need to integrated the data as it seems to similar but coming from the different sources. Validation is required at all the design phases of the development of the data warehouse. With the rapid developm...

Data warehouse is considered as the core component of the modern decision support systems. Due to the major support of data warehouse in the daily transaction of an enterprise, the requirements for the design and the implementation of DW are dynamic and subjective. This dynamic nature of the data warehouse may reflect the evolution in the data warehouse. Data warehouse evolution may be focused ...

Data warehouses collect data from multiple remote sources and integrate the information as materialized views in a local database. The materialized views are used to answer queries that analyze the collected data for patterns, anomalies, and trends. This type of query processing is often called on-line analytical processing (OLAP). So that OLAP queries can be posed and answered easily, the data...