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Programs

Digital Marketing

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Visualization software tools in marketing

  • Class 30
  • Practice 30
  • Independent work 120
Total 180

Course title

Visualization software tools in marketing

Lecture type

Elective

Course code

20-04-003

Semester

3

ECTS

6

Lecturers and associates

Course objectives

The course aims to introduce students to the basic techniques of visualization and exploratory data analysis. It is a necessary theoretical and practical knowledge and skills in the field of digital marketing that is characterized by large volumes of data. Apart from technique, students are introduced to a variety of tools for visualization and exploratory data analysis.

Content

Introduction to data visualization. The visual apparatus. The most common errors in data visualization. Types of visualization tools. Analytical interactions: comparison, sorting and grouping, aggregation, change the definition of variables. Analysis of the structure, distribution and time series. Forecasting. Analysis of deviations and correlations. Spatial analysis. Dashboards for visualization and exploratory analysis.

Required reading

1. Few, S. : Now You See It: Simple Visualization Techniques For Quantitative Analysis, Analytics Press, 2009.

Additional reading

2. Tufte, E. : Visual Display Of Quantitative Information, Graphics Pr, 2001.
3. Ware, C.: Information Visualization: Perception for Design
Morgan Kaufmann Publishers Inc. San Francisco, 2004.

Minimal learning outcomes

  • Select a tool for visualization and exploratory analysis of a given problem and correct visualization errors in the given examples.
  • Critically interpret the techniques of analytical interaction and navigation in given examples.
  • Critically interpret analytical patterns used in the given examples.
  • Prepare data from a single data source for visual analysis and implement an interactive dashboard.

Preferred learning outcomes

  • Evaluate and critically interpret visualization design and achieve graphical integrity of given example by using the selected tool.
  • Select and apply appropriate techniques of analytical navigation and interaction for a given problem.
  • Select, apply and evaluate appropriate analytical patterns for a given problem.
  • Link data from multiple sources for visual analysis and implement complex interactive dashboard.
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