ACC 430 - 7-1 Project Part I
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Southern New Hampshire University *
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430
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Accounting
Date
Feb 20, 2024
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docx
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6
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Bryan Levin
ACC 430
7-1 Project
12/10/2023
Microsoft Excel Power Query/Power BI and Tableau tools have found several problems within the data sets provided. Duplicate payments are one of the problems present. In the analysis of the data set for Lab 6-3, it presented duplicate payments within the data. The Power Query/Power BI software was used to filter the data to demonstrate the duplicate payments. With
the Tableau software we were able to create a visual data set that clearly showed the duplicate payments. With the demonstration of the duplicate data, it helped in understanding why the numbers were distorted. Cost variance was another issue that we came across. Through Power Query/Power BI and Tableau we are able to identify the points where the costs diverted from the expected amounts. In both software’s, the cost variance tools take the set values and use the VAR
function to take set values and return the variances of these set values. From there we took these variations and made them into visuals to have a better comprehension.
We must also take into consideration ethics when utilizing data software. Data security and its analysis is extremely important as privacy is a significant ethical concern. Without having
the proper safeguards in place, the privacy of an individual and entities that the data pertains to is
in serious trouble. There is also the ethical consideration of data accuracy. The data needs to be accurate in order to make sure that acquire incorrectly or tampered with. We need to make sure that there is no bias when it comes to the method in which the data is collected. If there is any bias within the data, then it will skew the data and make it unable to be used. We need to make sure that the data is also cleaned. Clean data corrects or removes any corrupt, duplicate, incorrect, improperly formatted, or incomplete data. It allows the user to user to use the informational output from the analysis for practical purposes that included making decisions and solutions from the information. If the data is not cleaned, then it is hard to trust the validity of the
data, being that the data is so large. Data cleaning offers a level of confidence to the user that the information provided is accurate.
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Recommended textbooks for you
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