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Regular version of the site
Bachelor 2021/2022

Data Visualization

Type: Compulsory course
Area of studies: Business Informatics
When: 2 year, 1 module
Mode of studies: distance learning
Online hours: 15
Open to: students of one campus
Instructors: Irina Nikiforova / Nikivincze
Language: English
ECTS credits: 4
Contact hours: 48

Course Syllabus

Abstract

The growing availability of informative datasets and software tools has led to increased reliance on data visualizations across many areas. Data visualization provides a powerful way to communicate data-driven findings, motivate analyses, and detect flaws. This course will give you the skills you need to leverage data to reveal valuable insights.
Learning Objectives

Learning Objectives

  • The purpose of "Data Visualization" discipline is to master modern applied visualization tools (Excel, Power BI and Tableau), familiarization with different types of graphs, their construction and organization in reports and dashboards. The objectives of mastering the discipline "Data Visualization" are: 1) to be able to choose the right method of data visualization, 2) to gain experience using visualization tools (Excel, Power BI and Tableau) and 3) to practice organizing reports and dashboards with visualization results.
Expected Learning Outcomes

Expected Learning Outcomes

  • to be able to create dashboards using Power BI and Tableau software
  • to be able to create interesting, informative and creative stories using data
  • to know basic approaches and methods of data visualization
  • to know the basic rules of effective design and presentation of data
Course Contents

Course Contents

  • Introduction to Data Visualization
  • Methodology of Data Visualization
  • Basic Types of Visualization
  • Principles of Figure Design
  • Basic Graphs in Power BI
  • Dashboard Design in Power BI
  • Basic Graphs in Tableau
  • Dashboard Design in Tableau
  • Data Storytelling
Assessment Elements

Assessment Elements

  • non-blocking Exam
  • non-blocking Home tasks
Interim Assessment

Interim Assessment

  • 2021/2022 1st module
    0.6 * Home tasks + 0.4 * Exam
Bibliography

Bibliography

Recommended Core Bibliography

  • Brent Dykes. (2020). Effective Data Storytelling : How to Drive Change with Data, Narrative and Visuals. Wiley.
  • Nathalie Henry Riche, Christophe Hurter, Nicholas Diakopoulos, & Sheelagh Carpendale. (2018). Data-Driven Storytelling. A K Peters/CRC Press.
  • Walny, J., Frisson, C., West, M., Kosminsky, D., Knudsen, S., Carpendale, S., & Willett, W. (2019). Data Changes Everything: Challenges and Opportunities in Data Visualization Design Handoff.

Authors

  • NIKIFOROVA IRINA SERGEEVNA