Excel Test Out Materials - CumExam Data Sales House

Excel Test Out Materialse00 Cumexam Dataxlsxsales Datahouse Type Of

Open the existing workbook provided, save it under a new name, perform preliminary modifications, calculate profit and bonus eligibility, convert data to a table, analyze house types and sales trends with charts, finalize formatting, and then save and submit the completed workbook.

Paper For Above instruction

The task begins with opening the provided Excel workbook, which contains sales data related to house purchases. The initial step involves saving the file with a new name to preserve the original data. Subsequently, modifications are made to improve clarity and organization: adjusting column widths, inserting a header row with a descriptive title, applying formatting styles, and freezing header rows for ease of navigation. These preliminary steps set the foundation for a more in-depth analysis.

Next, the workbook requires calculating total costs and profits for each sale. New columns titled 'Total Cost' and 'Profit' are inserted immediately after the 'Sale Price' column. Formulas are implemented: the total cost is computed by summing purchase price and renovation costs, while profit is the difference between sale price and total cost. An additional cell evaluates whether each sale qualifies for a year-end bonus by checking if the profit exceeds $50,000, displaying "Yes" or "No" accordingly. These formulas must be copied down for all records to ensure accurate calculations across the data set.

The dataset is then transformed into a table named 'Date' with a specified style, which enables easier analysis and formatting. A total row is added to sum the number of houses sold for each house type, facilitating the analysis of sales distribution. Moving into specific data insights, a pie chart is created to visualize the total number of houses sold by type, with stylistic adjustments such as applying a predefined style, positioning the legend, exploding the largest segment, and adding data labels with callouts. These visualizations help identify which house types are most popular.

Further, the monthly sales trend is analyzed by calculating total house sales per month and converting these into a line chart with specified styling. The chart is repositioned for clarity, titled "Total Sales," and its line color adjusted to white, providing insight into seasonal fluctuations in house purchases. To enhance the analysis, a new column titled 'Sparkline' is added next to 'House Type' in the data table. Sparklines are inserted for each house type across the 12 months, offering a compact visual trend indicator directly within the data table.

Finally, the workbook requires formatting adjustments for professional presentation: setting the page orientation to landscape, inserting a footer with specific information (instructor's name, current date, user's name), and saving the final version. These steps ensure the workbook is polished and ready for submission, providing a comprehensive analysis of sales data, trends, and profitability for the company's project managers and stakeholders.

References

  • Microsoft. (2016). Excel 2016 for Beginners. Microsoft Support. https://support.microsoft.com/en-us/excel
  • Heizer, J., Render, B., & Munson, C. (2020). Operations Management (12th ed.). Pearson.
  • Steinberg, M. (2018). Mastering Excel Formulas and Functions. Wiley.
  • Gaskins, J. (2017). Data Analysis with Excel. Packt Publishing.
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  • Chen, M., & Chang, P. (2015). Business Data Analysis Using Excel. Springer.
  • Sharma, R. (2021). Practical Excel Data Analysis. Springer.
  • Excel Easy. (2023). Excel Charts and Graphs. https://www.excel-easy.com/examples/charts.html

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