Russom's (2006) article on the consequences of poor-quality data and the advantages of high-quality data

Essay by ontherun2_00@yahoo.cUniversity, Master'sA+, July 2007

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Russom's (2006) article talks about the consequences of poor-quality data and the advantages of high-quality data. In your view, to what extent are the data-quality statistics in Figures 1 through 4 in the article consistent with your organization's data quality situation? Discuss at least two different ways that database management software like Microsoft® Access® can help an organization avoid or reduce data-quality problems mentioned in the articleRussom (2006) points out that there was a trend toward paying more attention to the quality of data being used in the workplace between 2001 and 2005 following a change in responses to whether this data affected "losses, problems or costs", which makes sense. Data is great to have, but if you're working with data of poor quality, then your statistics will be off and thus unreliable.

One of the points touched on by Russom (2006) that struck home for me in terms of my organization is losing credibility due to poor data quality.

As HRIS for the entire Alaska region, we maintain quite a bit of data on our employees. If we make data entry mistakes (figure 1), statistics will be off on the departmental 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 simple data entry of an evaluation score. We enter performance evaluations on employees, which then generates their merit raise for the year. If we score them above or below their actual rating (data entry error) and they get an incorrect raise, that affects the employee (paid less or more), the department (the budget was impacted by less or more), and payroll (they need to retro pay or take back money)…all from one error. We have remedied much...