FI1BBSF05 Spreadsheet Fundamentals

FI1BBSF05 Spreadsheet Fundamentals

  • Course description
    • Course code
      FI1BBSF05
    • Level of study
      5.1
    • Program of study
      Data Analyst 2
    • Credits
      5
    • Course coordinator
      Bertram Haskins, Alec Du Plessis
Teaching term(s)
2024 Autumn
Authors
Alec Du Plessis
About the Course

This course teaches a foundation level introduction to the spreadsheet work environment, specifically the Microsoft Excel suite. Candidates will learn how to use the program from a basic operational basis until they are able to effectively gather, clean, manage, and organize data within the Excel framework. Candidates will learn how to import and export data from Excel from or into other platforms, specifically how to prepare data into a comma-separated values file (.csv) format for use in open-source analytical tools such as Python or R based systems. Additionally, Candidates will be introduced to online cloud-based spreadsheet tools like Google Sheets which encourages a multi-user collaborative workplace environment.

This course is relevant to the program because it teaches the first and most accessible data analysis tools: spreadsheets. Candidates will learn the basics of two spreadsheet suites, which will cover data collection, cleaning, sorting, management, and use. The course is designed to teach the software suits from zero prior knowledge.

Course Learning Outcomes
Learning outcomes - Knowledge

The candidate:

  • has knowledge of concepts and process that are used to gather, clean, manage, and organize data inside a spreadsheet software package
  • has knowledge in data management techniques such as storing, sorting, and presenting data using expressions
  • has knowledge in cloud based spreadsheet software such an Google Spreadsheets
  • has knowledge in data flow pipelines to link spreadsheet software to external data tools
  • understands the underlying principles of why spreadsheets are useful in a societal and value-creation perspective
Learning outcomes - Skills

The candidate:

  • can apply knowledge of spreadsheet software to gather, sort, store, manage and organize data in a visually representable way
  • can apply knowledge in spreadsheet tools such as conditional formatting, and pivot tables to summarize key data points
  • can find information and material to develop a transformative spreadsheet project
  • can study material related to spreadsheet software as used in industry
  • masters two spreadsheet software suites, one offline and one online
  • masters the basic workbook manipulation tools in the latest version of spreadsheet software
  • masters the data input and output systems within spreadsheets to allow data to be interfaced between the program and external analytical tools
  • masters the use of basic field formulas to assess and automate traditionally manual data tasks
General Competence

The candidate:

  • can create workbooks to manage data from start to finish manually based on the needs of selected target groups
  • can build relations with clients that use real world data sets and solve problems with spreadsheet tools
  • can develop methods to deliver collaborative workbooks using an online cloud-based spreadsheet software
Teaching and Learning

In this course, the following teaching and learning methods can be applied, but are not limited to:

  • Lecture: Educator-led presentations or activities providing knowledge, skills, or general competencies in the subject area.
  • Group work: Collaborative activities where students work together to solve problems or complete tasks.
  • Tutoring: One-on-one or small group sessions with an instructor for personalized guidance and support.
  • Student presentations: Opportunities for students to demonstrate their understanding of course material by presenting to peers.
  • Online lessons: Digital content delivered via an online learning platform.
  • Guidance: Individualized advice and direction from instructors to support students in their learning journey.
  • Workshops: Practical sessions focused on hands-on application of theoretical concepts or skills.
  • Self-study: Independent study where students engage with course material on their own without any teacher support.
Reading list

Teaching materials, reading lists, and essential resources will be shared in the learning platform and software user manuals where applicable.

Assessments
Form of assessmentGrading scaleGroupingDuration of assessment
Course Assignment
Pass / Fail
Group/Individual
1 Week(s)
Approved by
x.x
Accreditation
x.x