Data Quality Business Case

Data Quality Business Case - Thomas C. Redman Impact of...

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COMMUNICATIONS OF THE ACM February 1998/Vol. 41, No. 2 79 As practitioners know, creating awareness of a problem and its impact is a critical first step toward resolution of the problem [ 5 ] . The needed awareness of poor data quality, while growing, has not yet been achieved in many enter- prises. After all, the typical executive is already besieged by too many prob- lems, low customer satisfaction, high costs, a data warehouse project that is late, and so forth. This article aims to increase awareness by providing a sum- mary of the impacts of poor data quality on a typical enterprise. These impacts Thomas C. Redman Poor data quality has far-reaching effects and consequences. The Impact of Poor Data Quality on the Typical Enterprise
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include customer dissatisfaction, increased opera- tional cost, less effective decision-making, and a reduced ability to make and execute strategy. More subtly perhaps, poor data quality hurts employee morale, breeds organizational mistrust, and makes it more difficult to align the enterprise. Poor data quality and its underlying causes are potent contrib- utors to an “information ecology” [ 2 ] inappropriate for the Information Age. Further, leading enterprises have demonstrated that data quality can be dramat- ically improved and the impacts mitigated. Readers are referred to other articles in this section and to [ 7 ] for case studies and techniques for doing so. Naturally enough, the particulars vary from enter- prise to enterprise. Perhaps the most important point is that many of the problems facing today’s executive have poor data quality at their roots. A practitioner can often create awareness by showing how poor data quality contributes to the better-known problems. This is often more effective than estimating error rates and following errors to determine the consequences. An estimate of data accuracy levels in a typical enterprise is given in the following section; subse- quent sections describe impacts at the operational, tactical, and strategic levels. 1 A number of examples from Fortune 100 companies are cited (though the identities of these companies are not given). Data Quality Issues and Data Accuracy Over the last several years, more and more references to poor data quality and its impact have appeared in the news media, general-readership publications, and technical literature [ 7, 11 ] . An enterprise may have a wide array of data quality problems. One way to categorize these issues is as follows [ 7 ] : • Issues associated with data “views” (the models of the real world captured in the data), such as rele- vancy, granularity, and level of detail. • Issues associated with data values, such as accu- racy, consistency, currency, and completeness. • Issues associated with the presentation of data,
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This note was uploaded on 02/16/2011 for the course INFORMATIO 0200 taught by Professor N during the Spring '11 term at Pittsburgh.

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Data Quality Business Case - Thomas C. Redman Impact of...

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