Summary: This Project Will Determine Core Courses

Summaryin This Project You Will Determine What Core Courses That Are

In this project, you will determine which core courses are required to complete your degree in Information Systems Management. You will identify the courses offered and estimate how much longer it will take to graduate. By completing a pivot table and chart, you will visually analyze course availability and identify which semester offers the most relevant courses for your graduation plan. The process involves opening the Excel workbook, creating a pivot table by highlighting the entire data set, and placing it on a new worksheet. You will sort the pivot table to move Student level to the column labels, change Year to show a count of courses, and set Course as the row label. A column chart will be inserted with specific design settings. The chart's title should be "Course Availability," and the worksheet should be named "Course Availability." Further, you will generate a pivot chart based on the data, filter by Year, and set Courses on the axis with the count of students as values. The chart type should be columns, styled appropriately, and titled "Course Overview." After editing the chart to include two additional courses, you will rename the worksheet accordingly, save, close, and exit Excel.

Paper For Above instruction

The process of planning degree requirements in Information Systems Management through quantitative tools such as pivot tables and charts allows students and academic advisors to make informed decisions regarding course scheduling and program completion timelines. This approach streamlines the analysis of course offerings across semesters and enables students to identify which courses are available and prioritize enrollment strategies for efficient graduation. Creating a pivot table from the course dataset involves selecting the entire data set and organizing it to display relevant fields such as Student Level, Year, and Course.

The organization of the pivot table aims to facilitate the analysis of the distribution of courses across different student levels and academic years. Moving the Student Level into the column labels provides a clear comparison across student categories, whereas changing Year to display the count of courses offered allows for understanding the semester-wise course load. Setting Courses as row labels helps in tracking specific courses and their frequency across the dataset. The visualization process complements the data analysis by offering a graphical overview of course availability over time.

Inserting a column chart with the specified design layout enhances interpretability, providing a visual summary of course offerings. Naming the chart “Course Availability” and the worksheet “Course Availability” ensures clarity in presentation. Furthermore, generating a pivot chart based on the data, filtering by Year, and positioning Courses on the axes offer dynamic insights into course availability trends. Changing the chart type to columns and styling it to match institutional preferences improves clarity and aesthetic appeal.

The addition of two new courses to the dataset and the subsequent adjustment of the chart serve as practical exercises in maintaining and updating visual data representations. Renaming the worksheet to “Course Overview” and saving the workbook encapsulates the process of creating a comprehensive visual dashboard for course planning. By employing these data visualization techniques, students can better understand and manage their academic pathways, ultimately aiding in timely graduation and minimizing course scheduling conflicts.

References

  • Cormack, A. (2018). Excel Data Analysis: Your visual blueprint for analyzing data, charts, and PivotTables. John Wiley & Sons.
  • Few, S. (2009). Now You See It: Simple Visualization Techniques for Quantitative Data. Analytics Press.
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  • Microsoft Support. (n.d.). Create a PivotTable to analyze worksheet data. Retrieved from https://support.microsoft.com/en-us/excel
  • Few, S. (2012). Information Dashboard Design: The Effective Visual Communication of Data. O'Reilly Media.
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  • Schneiderman, B., & Plaisant, C. (2006). Designing the User Interface: Strategies for Effective Human-Computer Interaction. Pearson Education.

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