Data Quality in Data warehouse: problems and solution
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 1
Abstract
In recent years, corporate scandals, regulatory changes, and the collapse of major financial institutions have brought much warranted attention to the quality of enterprise data if we can better understand the problems of quality issues, then we can develop a plan of action to address the problem that is both proactive and strategic. Each instance of a quality issue presents challenges in both identifying where problems exist and in quantifying the extent of the problems. Quantifying the issues is important in order to determine where our efforts should be focused. It is reported that more than $2 billion of U.S. federal loan money had been lost because of poor data quality at a single agency. It also reported that manufacturing companies spent over 25% of their sales on wasteful practices. 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 along with their possible solution. problems in different phase of data warehouse i.e.; data sources, data integration & data profiling, Data staging and ETL, data warehouse modeling & schema design are discussed in this paper. The 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 give some classification of these causes as well as solution for improving data quality through Statistical Process Control (SPC),Quality engineering management . etc I 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 company on India. I 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.
Authors and Affiliations
Rahul Kumar Pandey
Keywords
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