COMS 1130: Introduction to Spreadsheets and Databases

Course
Computer Science
Teaching
A foundational course on Microsoft Excel and Access for data analysis, modeling, and database management.
Published

January 10, 2025

Introduction to Spreadsheets and Databases

Credits: 3
Institution: Iowa State University
Format: In-Person Course (Offered Fall & Spring)

COMS 1130 is a 3-credit undergraduate course that teaches essential skills in Microsoft Excel and Microsoft Access, emphasizing hands-on, real-world applications of data management and analysis.

Course Overview

This course introduces students to data organization, analysis, and decision-making using Microsoft Excel and Access. Through a project-based approach, students learn to create, analyze, and manage data models for business, engineering, and academic applications.

Learning Objectives

By the end of this course, students will be able to:

  • Apply Microsoft Excel and Access tools to solve real-world analytical problems.
  • Conduct data modeling, statistical analysis, and visualization.
  • Build, manage, and query relational databases and structured datasets.

Topics Covered

Microsoft Excel (Spreadsheets)

  • Create and format spreadsheets
  • Apply mathematical, statistical, logical, and lookup functions
  • Build charts and data visualizations
  • Use PivotTables and subtotals for data summarization
  • Conduct What-If Analysis
  • Import and export spreadsheet data
Microsoft Excel Spreadsheets

Figure 1: Spreadsheet data analysis and visualization in Microsoft Excel.

Microsoft Access (Databases)

  • Design relational tables and define relationships
  • Create forms, queries, and reports
  • Sort, filter, and update records
  • Implement data validation
  • Perform decision-making tasks based on database queries
Microsoft Access Databases

Figure 2: Relational database design and querying using Microsoft Access.

My Role

Computer Science Graduate Teaching Assistant (Fall 2024)

As a Teaching Assistant for COMS 1130, I supported this large foundational course through lab instruction, mentorship, and assessment. My responsibilities included:

  • Lab Instruction & Demonstrations: Conducted in-person labs on Excel and Access, showcasing real-world applications of data tools.
  • Student Mentorship: Provided one-on-one support during labs and office hours, helping students navigate complex formulas, queries, and project workflows.
  • Content Support: Responded to student queries on Canvas and via email, ensuring timely and clear communication.
  • Assessment & Feedback: Evaluated assignments, projects, and practical exams, providing actionable feedback.
  • Course Coordination: Collaborated with the course instructor to improve teaching materials and lab engagement strategies.

This role strengthened my expertise in data analysis education, practical software instruction, and student mentoring, helping learners build analytical fluency essential for both academic and professional growth.