Data quality can be assessed in terms of several issues, including accuracy, completeness, and consi

May 19th, 2016
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Data quality can be assessed in terms of several issues, including accuracy, completeness, and consistency. Are each of the above three issues, discuss how the assessment of data quality can depend on the intended use of the data, giving examples. Propose two other dimensions of data quality.

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Running Head: DATA QUALITY1Data QualityNameInstitutional AffiliationDATA QUALITY2Data quality assessment is the scientific and statistical analysis of data so as to find out ifdata gotten from environmental data operations are of the right type, quality, and quantity tosupport the intended use. The quality of data is meaningful only when it has an exact or closerelationship with the intended use of the data (Guptill, Morrison, 2013).Normally, there is no commonly acceptable definition of data quality and therefore moststatistics define data quality regarding fitness for use that is how that particular data fits theintended use or purpose. Whether or not data are fit for using it, all depends on the intended usesand particular characteristics of data. The workability of this policy depends on the provision ofnecessary information which helps the users to determine the fitness of their intended use (Karplus,Diederichs, 2012).For instance, the following six dimensions of quality have been recognized to be usedwithin the concept of fitness for use or the intended purpose.The first one is the relevance of the statistical data which mirrors the extent which that

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