A Descriptive Classification of Causes of Data Quality Problems in Data Warehousing
Data warehousing is gaining in eminence as organizations become awake of the benefits of decision oriented and business intelligence oriented data bases. However, there is one key stumbling block to the rapid development and implementation of quality data warehouses, specifically that of warehouse data quality issues at various stages of data warehousing. Specifically, problems arise in populating a warehouse with quality data. Over the period of time many researchers have contributed to the data quality issues, but no research has collectively gathered all the causes of data quality problems at all the phases of data warehousing Viz. 1) data sources, 2) data integration & data profiling, 3) Data staging and ETL, 4) data warehouse modeling & schema design. The state-of-the-art purpose of the paper is to identify the reasons for data deficiencies, non-availability or reach ability problems at all the aforementioned stages of data warehousing and to formulate descriptive classification of these causes. We have identified possible set of causes of data quality issues from the extensive literature review and with consultation of the data warehouse practitioners working in renowned IT giants on India. We hope this will help developers & Implementers of warehouse to examine and analyze these issues before moving ahead for data integration and data warehouse solutions for quality decision oriented and business intelligence oriented applications.
Keywords: Data Quality (DQ), ETL, Data Staging, Data Warehouse
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