Comparing Microsoft Power BI and Tableau for Data Analytics

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Southern New Hampshire University *

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430

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Accounting

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Apr 3, 2024

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Violet Bass Southern New Hampshire University ACC 430 Data Analytics for Finance Professionals 7-1 Project: Data Storytelling Part I Microsoft Excel Power Query/Power BI versus Tableau Comparison Report and Evaluation Checklist Don Majors [February 22, 2024]

7-1 Project: Data Storytelling Companies use data analytics to solve specific problems. The first problem is using satellite images to predict city growth and find a good business opportunity. The second problem is helping workers on the front lines. Companies like Coca-Cola use data programs to make work easier for these workers and increase productivity. The third common problem is dealing with large and messy data sets. To solve this, companies use tools like Microsoft Power BI and Tableau Desktop. These tools help organize and clean the data, making it easier for companies to understand and use their goals. Techniques The company is thinking about using either Microsoft Power BI or Tableau, two software options for doing-in-depth analysis. Each software has its pros and cons. This report is a detailed analysis of two software options. The goal is to recommend the best product for companies by looking closely at the differences and similarities between Power BI and Tableau. These programs help us organize our data using different techniques. For e, in Module 4 Lab 6-3, we used them to find duplicate payments in a big set of data. This same idea can be used by businesses to check for duplicate invoices and make sure their financial statements are accurate. Data analytics programs are also useful for figuring out how productive we are. In Module 4 Lab 7-1, we evaluated job costs using these programs. We added a new measure to go through the data and create visuals to make the information clear for any audience we’re presenting to. Throughout the course, we use these techniques in various labs to have clean and necessary data for the story we want to tell.

The picture on the left is the dashboard of Tableau, on the right is Microsoft Power BI Ethical issues When understanding data analytics better, you realize how crucial it is to be ethical. Handling a lot of data requires sticking to principles like respecting privacy, avoiding bias, and making sure the information is correct. The most important thing is to keep the data secure and private because it has sensitive company info and maybe personal details of clients. It’s not appropriate for anyone to access this data without permission. Accuracy also plays a vital role, both the data I put and look at should be up-to-date and correct. Making decisions based on old or wrong data could cause serious money problems for companies. Clean data After reading this report, the company will really understand what Microsoft Power BI and Tableau can do for data analytics. The team knows that each software has its own strengths. Power BI is great for making visuals and dashboards, while Tableau is excellent for exploring and discovering data. To decide which software is best, the company needs to be clear about its

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specific needs and goals. The company will learn how these software tools can solve problems and use different techniques in data analytics. It will also understand the importance of being ethical with data and having clean data for accurate analysis. Clean data is crucial for giving the right information for analysis. The report shows how both Power BI and Tableau can spot anomalies or errors in the data, using things like box plots and scatter plots. Anomalies and Problems Some companies have duplicated payment or recorded twice by mistake. This happened because we didn’t check the invoice numbers properly. We used both Power Bi and Tableau to see and understand these double payments. In Power BI, we did a bit more work. We added extra columns, filtered the data, and made a separate sheet showing the duplicate payments with formulas. Tableau’s process was simpler. We transformed the data to understand it better, and we created a visual representation showing where the duplicate payments were. Even though the steps were a bit different, both Power BI and Tableau gave us similar results in solving and showing the issue of duplicate payments. The second challenge was using the software to check how much it costs for the organization to do a job. This needed us to look at various things like overhead, profit, labor, and how much the company likes or dislikes certain things. Both software programs helped us see the connection between how much the company likes or dislikes something and the costs it has. Quantitative Methods Application Thinking about numbers, especially quantitative statistics, is crucial. It helps us check how well things are going, find connections, and spot issues in the company. Using these statistical tools lets the company do things like regression analysis, which give insights into how

the company might perform and if it’s meeting the goals set by the top management. Another useful tool is profiling. This helps the organization look closely at specific sets of data, making it easier to find anything unusual. After that, we can analyze this data to understand how it affects the organization. Both Microsoft Power BI and Tableau are good for these kinds of quantitative analyses and profiling. Clustering is another cool tool available in both Power BI and Tableau. It gives us a clear picture, especially when we're talking about job costs in the organization. Both products show great potential, proving their effectiveness in various job-related analyses done within the organization. Summary and recommendations Microsoft Power BI is good for quick data access and has great visual for decision making, but it can take time for complex data. Tableau is excellent at creating powerful visuals quickly, user-friendly, and efficient for large datasets. I would recommend Tableau because it has advanced features, works effectively, and gives accurate results when exploring more data. Its ability to make visual results quickly was a big reason for our choice. Choosing Tableau helps companies make better decisions based on data.

References Richardson, V. J., Terrell, K., & Teeter, R. (2023). Data Analytics for Accounting . McGraw Hill.

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