Towards Data Quality into the Data Warehouse Development
Munawar Munawar, Naomie Salim, Roliana Ibrahim
Abstract
Munawar Munawar, Naomie Salim, Roliana Ibrahim
Abstract
Commonly, DW development methodologies, paying little attention to the problem of data quality and completeness. One of the common mistakes made during the planning of a data warehousing project is to assume that data quality will be addressed during testing. In addition to the data warehouse development methodologies, we will introduce in this paper a new approach to data warehouse development. This proposal will be based on integration data quality into the whole data warehouse development phase, denoted by: integrated requirement analysis for designing data warehouse (IRADAH). This paper shows that data quality is not only an integrated part of data warehouse project, but will remain a sustained and ongoing activity.
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Commonly, DW development methodologies, paying little attention to the problem of data quality and completeness. One of the common mistakes made during the planning of a data warehousing project is to assume that data quality will be addressed during testing. In addition to the data warehouse development methodologies, we will introduce in this paper a new approach to data warehouse development. This proposal will be based on integration data quality into the whole data warehouse development phase, denoted by: integrated requirement analysis for designing data warehouse (IRADAH). This paper shows that data quality is not only an integrated part of data warehouse project, but will remain a sustained and ongoing activity.
Key concepts: Data warehouse, Computer science, Data quality, Quality (philosophy), Data integration, Database, Completeness (order theory), Data science