Dataset Visualization 04 – Filter

Main Idea

In this scenario, participants learn how to visualize datasets for later use in various application. In this part, they will learn how to effectively filter datasets to extract specific information and conduct detailed analyses.

Creator Lana Sattelmaier
Subject Computer science
Length 45 – 60 minutes
Pedagogical Approach

Experiential learning, Project-based Learning

  • C29 Visualization of Datasets
  • C18 Problem solving through tools
  • C21 Data collection
Grades Grades 11 – 12

Computer with internet access and Tableau Desktop or similar software.


Observe student engagement and proficiency in using the AI tools.


Learning Activities


Introduction to the Importance of Data Filtering and Its Application in Tableau Desktop, and Practical Application of Filtering Techniques to Refine and Specify Data Analysis.


LA1: Contextualization (10 min)

The teacher introduces the purpose of the task:

  • Introduction to the topic of data filtering and its significance for detailed data analysis.
  • Explanation of why data filtering is crucial for extracting relevant information from large datasets and conducting precise analyses.

LA2: Working Phase (30 min)

  • Students filter their results in the program:
    • Students open their datasets in Tableau Desktop and practice applying various filtering techniques.
    • Tasks include filtering data based on specific criteria, creating filter actions, and applying range filters.
    • Students are expected to apply different filters, observe and document their impact on data visualization.
    • Analysis of the filtered data and comparison of results with the original dataset to illustrate the significance and benefits of filtering.
  • Support from the instructor:
  • The instructor is available for questions and provides individual support.
  • Tips and guidance on efficiently applying filtering techniques in Tableau Desktop.

LA5: Outlook (5-30 min)

Discussion on what can be done with the datasets:

  • Discussion of the opportunities that data filtering opens up, such as identifying specific trends, focusing on relevant data points, and creating detailed reports.
  • Discussion on advanced analyses made possible by filtering and how these can be applied in real-world scenarios.
  • Reflection on what has been learned and how students can apply filtering techniques in future projects.


Worksheet: Here