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Data Clean-Up and Management by Kenneth Furuta, Margaret Hogarth

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19

Data quality policy

Abstract:

Poor data quality has serious consequences for an organization. Ideally, libraries can develop a culture of care and knowledge about data, its life cycle and data quality. Common errors can be identified and processes adjusted to minimize error rates. A data quality policy is best when viewpoints from the stakeholders are incorporated.

Key words

data quality policy

guidelines

errors

A typical organization has a data error rate of 1–5 percent, calculated as the number of erred fields/the number of total fields (Redman, 1998: 80). It is safe to assume that libraries have at least that error rate, but the rate is probably higher. As Thomas Redman reported in 1995, errors in data cost an institution, alienate ...

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