Data Warehouse Quality: A Review of the DWQ Project

Towards Quality-Oriented Data Warehouse Usage and Evolution

As a decision support information system, a data warehouse must provide high level quality of data and quality of service. In the DWQ project we have proposed an architectural framework and a repository of metadata which describes all the data warehouse components in a set of metamodels to which is added a quality metamodel, defining for each data warehouse metaobject the corresponding relevant...

DWQ Foundations of Data Warehouse Quality ( DWQ

Dwq : Esprit Long Term Research Project, No 22469 Foundations of Data Warehouse Quality Data Warehouse Connguration

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 de ned over the sources. When a query is posed, it is evaluated locally, using the materialized views, without accessing the original information sources....

Data Integration in Data Warehousing (Keynote Address)

Data integration is a central problem in the design of Data Wareshouses and Decision Support Systems. When data passes from the sources of the application-oriented operational environment to the Data Warehouse, possible inconsistencies and redundancies should be resolved, so that the warehouse is able to provide an integrated and reconciled view of data of the organization. Generally speaking, ...

Data Currency Quality Factors in Data Warehouse Design

A Data Warehouse (DW) is a large collection of data integrated from multiple distributed autonomous databases and other information sources. A DW can be seen as a set of materialized views defined over the remote source data. Until now research work on DW design is restricted to quantitatively selecting view sets for materialization. However, quality issues in the DW design are neglected. In th...