<![CDATA[AbstrakMany articles on data warehouse development have been written, however no clearly defined standards have been formulated that is applicable to all type of organizations. The rapid growth in data volumes has given rise to new problems for institutions: data quality, which is a critical issue when data are transferred from one system to another. Lack of data quality provided by data warehouse can lead to bad strategic decisions and indicates a significant failure rate. Thus, data quality in data warehouse needs to be assured. It has been widely accepted that data quality issues can emerge at any stage of data warehouse development. However, yet little work is done for formulating data quality that should be considered in the entirety of data warehouse development. This study was achieved through qualitative method by reviewing the most common practices data warehouse development in five organisations that is applicable to all type of organizations and then tried to confirm whether data quality in data warehouse from literature review is practiced in the five organisations followed by confirmation from the experts in order to determine specific data quality dimensions that correlated with data warehouse development. Based on the similirities in the development stages, identification of common practices for DW development can be obtained: requirements analysis, conceptual design, logical design, ETL, and physical design. There are sixteen dimensions of data quality that should be considered in the development of data warehouse.Keywords : data warehouse, data quality, common practices.]]>
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