Data Quality Requirements Analysis and Modeling

Excerpt from Data Quality Requirements Analysis and Modeling

Computerworld, September 28, 1992, p. 80-84. The Wall Street Journal, May 26, 1992, page B6. Just like the well publicized concept of zero defect products in the manufacturing literature.high for the vital few projects whereas the trivial many defects are not worth tackling because the cure costs more than the disease (juran Gryna, In sum, when the cost is prohibitively high, it is not feasible to attain zero defect data.

Given that zero defect data may not always be necessary nor attainable, it would be useful to be able to judge the quality of data. This suggests that we tag data with quality indicators which are characteristics of the data and its manufacturing process. From these quality indicators, the user can make a judgment of the quality of the data for the specific application at hand. In making a financial decision to purchase stocks, for example, it would be useful to know the quality of data through quality indicators such as who originated the data, when the data was collected, and how the data was collected.

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