Russoms (2006) article talks ab verboten the consequences of poor- flavor information and the advantages of high-quality data. In your view, to what boundary are the data-quality statistics in Figures 1 through 4 in the article consistent with your organizations data quality occurrence? prove at least two different ship canal that database prudence software like MicrosoftÂ® AccessÂ® can facilitate an organization avoid or reduce data-quality problems mentioned in the articleRussom (2006) points out that thither was a trend toward paying more assist to the quality of data being used in the work in the midst of 2001 and 2005 following a change in responses to whether this data abnormal ?losses, problems or costs?, which brightens sense. Data is gravid to have, but if you?re working with data of poor quality, wherefore your statistics will be off and thus unreliable. One of the points affected on by Russom (2006) that struck home for me in footing of my organization is lo sing credibility due to poor data quality. As HRIS for the entire Alaska region, we affirm quite a bit of data on our employees. If we make data entry mistakes (figure 1), statistics will be off on the discussion sectional level, the location (process level) level, the regional level, and across the entire organization, not to mention just for the employee who logs in to check their information.
Let?s take a unanalyzable data entry of an paygrade score. We enter performance evaluations on employees, which then generates their merit give rise for the year. If we score them supra or below their actual rate (data entry error) and they make an incorrect ra! ise, that affects the employee (paid less or more), the department (the budget was impact by less or more), and payroll department (they occupy to retro pay or take binding money)? altogether from one error. We have remedied much... If you want to get a amply essay, order it on our website: OrderCustomPaper.com
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