Acc 430 - Milestone One

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Southern New Hampshire University *

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430

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Accounting

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Feb 20, 2024

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ACC 430: Data Analytics for Financial Professionals Milestone One Southern New Hampshire University Bryan Levin 11/12/23
Data analytics solutions such as Microsoft Excel Power Query/Power BI and Tableau are flexible and can be used to solve data related issues. These solutions can be used in analyzing ethical issues, explaining techniques, explaining why clean data is being used, identifying problems, and justifying why identifying anomalies is important when working with data. The accounting department has data that is frequently inconsistent in format, missing numbers, and outliers. There can be an overabundance of data when one starts to look at the data for the company. The data needs to be broken down and cleaned up to be able to be analyzed properly to see the exact information that one is looking for. The technologies aid in the creation of models that forecast cost variations. The models are also able to help the management department discover the problem areas, by measuring key performance indicators with industry data and real-time industry data. Microsoft Excel Power Query/Power BI and Tableau are two examples of analytical technologies that can help the accounting department in its daily operations. Power Query with Microsoft Excel Power BI can be utilized to clean and manipulate data. To be able to make the data usable, one may eliminate duplicates, fill in the missing information, and pivot data. The company analysts can use data preparation with Tableau to clean and restructure the data. As an example, one can aggregate data, combine various tables, and construct computed columns. Once the data has been cleaned and compiled, we can apply this data to do predictive analysis, such as estimating consumer behavior or sales. One can also use program languages such as R and Python to incorporate machine learning into Power BI and generate predictions. “Both R and Python are full programming languages with extensive capability for analyzing and manipulating data which can unlock more insights from your data. While Power BI can connect to many data
sources, there are a few that it lacks. R and Python are open source languages and as a result, have a plethora of packages and libraries which can be used to extend the language’s abilities. Some of these packages include dealing with specific data sources and file types. They are also capable of some useful visuals. Your organization may have existing solutions written in R or Python, and this code could easily be reused in Power BI. Or perhaps you are already an expert at R or Python. Rather than learning the in and outs of Power Query, you could largely by-pass it with a language you are already familiar with and fast at” (IterationInsights). We can use previous data with these languages to help predict sales. Both analytical approaches can be used to track performance after receiving the prediction analysis. The company will be able to build a real-time dashboard and stream data using Power BI to keep track of KPIs. It can be used to keep track of sales and website visitors in real time. Tableau allows the ability to employ data refresh schedules to keep dashboards current. An example of a data refresh would be monitoring inventory levels. These data analytics tools are great assets for those that are looking to use data to be able to make well informed decisions as they provide a wide range of features and the ability to address various data related difficulties. Numerous ethical concerns need to be thoroughly examined while dealing with data and analytical tools while trying to uphold ethical and open data practices. Privacy and transparency are two major ethical concerns in setting up an accounting department. Accountants regularly work with private financial information, such as a client or employee’s personal data. Data breaches, or misuse of data are serious violations of one’s privacy. It can ruin the confidence and reputation of a company if they revealed customer tax documents through the lack of data safeguards. If analytical tools are poorly established and monitored, it can inadvertently reinforce bias. As an example, an accounting department could implement a system that unjustly favors
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