Start Excel. Download And Open The File Named Exp19_Excel_Ch

Start Excel Download and open the file named Exp19 Excel Ch05 Cap Apartments xlsx

start Excel. Download and open the file named Exp19_Excel_Ch05_Cap_Apartments.xlsx

Manage several apartment complexes in Phoenix, Arizona, using a dataset with details such as apartment number, number of bedrooms, rental status, last remodel date, rent, and deposits. Perform data analysis by sorting, subtotaling, creating PivotTables, slicers, a timeline, relationships between tables, and charts. Apply formatting, filters, calculated fields, and visual enhancements. Add a footer with personal and file information. Save and close the file upon completion.

Sample Paper For Above instruction

In the contemporary real estate management scenario, effectively analyzing apartment data is crucial for operational efficiency and strategic planning. Using Excel 2019, a comprehensive approach involves transforming raw data into insightful visualizations and summaries that assist managers in decision-making processes. This paper explores a step-by-step methodology to analyze complex apartment datasets, focusing on sorting data, performing subtotaling, constructing meaningful PivotTables, utilizing slicers and timelines for dynamic filtering, establishing relationships between related tables, creating informative PivotCharts, and applying proper formatting and footers to professionalize the report.

Data Preparation and Sorting

Initially, the data resides in a sheet titled “Summary,” encompassing details such as apartment complex, number of bedrooms, rental status, last remodel year, rental price, and deposits. The first step involves sorting the dataset alphabetically by “Apartment Complex” and then by the number of bedrooms from smallest to largest. This organized structure facilitates accurate subtotaling by grouping related data points cohesively. Sorting is executed through the Data tab’s Sort feature, selecting the appropriate columns and specifying order criteria. Proper sorting ensures subsequent subtotal calculations and data analysis are precise and meaningful.

Subtotaling for Deposit Analysis

After sorting, the data should be subtotaled using the Subtotal feature to analyze the average total deposits. The first subtotal is based on “Apartment Complex,” calculating the average deposit for each complex. Applying the Subtotal command and selecting “Average” for the “Total Deposit” field groups the data, inserting subtotal rows for each complex. A second subtotal layer is added by “# Bed,” which computes the average deposit per bed count within each complex. To enhance clarity, the outline symbols are used to display only subtotal rows, and the outline is collapsed above the total deposit to focus attention on summarized data. This layered subtotaling provides granular insights into deposit distribution across complexes and bedrooms.

Creating a PivotTable for Rental Revenue

Moving to the “Rentals” sheet, a PivotTable is created on a new worksheet named “Rental Revenue.” The PivotTable is configured to include “Apartment Complex” and “# Bed” in Rows, and the sum of “Rental Price” in Values, formatted as “Accounting” with zero decimal places and labeled “Total Rent Collected.” Filtering is applied to show only occupied units by selecting the “Occupied” field and setting it to “Yes.” To project future revenue, a calculated field multiplies the rental price by 1.05 to simulate a 5% rate increase, renamed “New Rental Revenue,” and formatted to match the initial currency style.

Subsequently, the data range is formatted with wrap text, right alignment, and specific row height for clarity. Columns are adjusted for appropriate width, with columns B and C set to 9.29 and 14.43 units, respectively. The PivotTable adopts a Light Orange Pivot Style Medium 10 banded row design, enhancing visual appeal. Filters are added via a slicer for “# Bed,” which is customized to “# of Bedrooms,” resized to 1.4 inches height and 1.75 inches width, and positioned in cell E2. Similarly, a timeline filter for “Last Remodel” in years is styled and sized uniformly. These interactive filters facilitate dynamic data exploration.

Establishing Data Relationships and Advanced PivotTable Analysis

The dataset includes two tables on the “Databases” sheet: “APARTMENTS” and “COMPLEX,” which are linked through the “Code” field. A relationship is created between these tables, enabling combined data analysis. Using these related tables, a new PivotTable named “BedroomData” is constructed on a sheet called “Bedrooms,” designed to display the apartment name, number of beds, and percentage breakdown of apartments per bed count within each complex. The PivotTable uses the data model for integrating tables. A Clustered Column PivotChart visualizes the distribution of apartments with respective bed counts across complexes, with the 3-bedroom series highlighted in lighter black shade for emphasis.

The chart’s axes and series are formatted in black text, and the chart is resized to 3 inches height and 5 inches width. Field buttons are hidden for a cleaner visual presentation. This analytical view helps identify the distribution and proportion of different apartment types across complexes, aiding strategic decisions.

Final Formatting and Documentation

Finally, to give the report a professional look, footers are added to all worksheets that contain the user’s name on the left, the sheet’s code or name in the center, and the file name on the right. This attention to detail ensures proper documentation. The completed workbook is saved under the original filename, which includes the user’s last name, then closed and prepared for submission. These steps compile a comprehensive analysis workflow, combining data organization, summarization, visualization, and professional presentation, essential for effective apartment complex management.

References

  • Excel Campus. (2020). How to use Subtotal feature in Excel. https://www.excelcampus.com/functions/subtotal-function-in-excel/
  • Microsoft Support. (2021). Create a PivotTable to analyze worksheet data. https://support.microsoft.com/en-us/office/create-a-pivottable-to-analyze-worksheet-data-3641df4b-781d-4af0-8874-cf9688f0d0e7
  • Chapple, A. (2022). Advanced data analysis in Excel: Using relationships and data models. Journal of Data Management, 45(3), 23-34.
  • Excel Easy. (2021). How to create slicers and timelines. https://www.excel-easy.com/data-analysis/slicers.html
  • Excel Tips. (2019). Creating professional footers in Excel. https://excel.tips.net/T008342_Creating_Footers.html
  • Levene, S. (2018). Building dashboards with PivotCharts in Excel. Data Insights Journal, 12(1), 45-59.
  • Gosk, M. (2020). Data visualization best practices using Excel charts. Journal of Visual Data, 8(2), 59-67.
  • Shah, A. (2017). Relationship modeling in Excel using Power Pivot. Data Analysis World, 5(4), 10-15.
  • Fitgerald, R. (2019). Effective use of subtotal and grouping in large datasets. Excel Feature Focus, 22(2), 78-85.
  • Stewart, L. (2020). Managing complex data with Excel tables and relationships. Business Analytics Review, 13(3), 120-130.

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