Data Visualisation and Visual Analytics


Amount of credits – 5.

Forms of the educational process – lectures, laboratory classes.

Form of final control – credit.


One of the most pressing challenges facing leading companies today is the processing and analysis of large volumes of structured and unstructured data in order to improve the quality of business decisions making. Visual analysis is a fast-growing promising area that combines the benefits of graphical visualization and the power of analytical computing when working with large masses of digital information. Data visualization allows you to identify patterns, trends, and correlations that may otherwise be left unnoticed in traditional reports or spreadsheets.

This course will allow you effectively use modern analytical tools and infographics to analyze complex, massive socio-economic phenomena and processes. You will learn how to make reasonable decisions based on pre-processing data and their interactive visualization.

Subject of the discipline: theoretical and practical questions concerning the economic interpretation of the results of the analysis of business processes and their interactive visualization on the basis of using of modern analytical methods and tools for infographic.

Purpose of the discipline: expansion and deepening of theoretical knowledge and acquisition of professional competencies in the visual analysis of business processes and effective decision making by using analytical methods and data visualization tools.

Task of the discipline:  

  • determine the key features visual analytics of complex socio-economic phenomena and processes;
  • acquaintance with the modern toolbase of data visualization;
  • study socio-economic phenomena and processes using analytical methods.
Subject learning objectives

After successful study of a discipline the student should be able to:

  • select the most effective data visualization tools to solve specific business tasks;
  • use infographic tools and choose analytical methods of information processing in conditions of changing information environment;
  • navigate the information space in order to collect the necessary data;
  • prepare information for processing by modern methods of business analytics;
  • interpret and present the results of analytical research;
  • prepare a report on the results of the conducted analytical researches.
Course intended learning outcomes

This subject also contributes specifically to the development of the following Course Intended Learning Outcomes – competencies:

  • ability to form qualitative research information space;
  • ability to use appropriately modern data visualization tools;
  • understanding the essence of solvable tasks with the help of methods of analytical processing of data and identifying trends;
  • ability to present qualitatively the results of analytical research for their further effective using.

Topic 1. Visual information in the information society.
Topic 2. Modern tools for data visualization. Infodesign.
Topic 3. Planning, collecting and preparing data for visualization. Overview of the sources of information.
Topic 4. Basics of business analytics. The main methods for processing digital information.
Topic 5. Economic interpretation of data visual analysis. Preparation of reports.

  1. Few, Stephen. Information Dashboard Design: The Effective Visual Communication of Data. Sabastopol, California: O’Reilly Media. 2006.
  2. Few, Stephen Show Me the Numbers: Designing Tables and Graphs to Enlighten. Oakland, California: Analytics Press. 2004.
  3. Tufte, Edward R. Visual Display of Quantitative Information, Second Edition. Cheshire, Connecticut: Graphics Press. 2001.
  4. Ware, Colin Visual Thinking for Design. Morgan Kaufmann, 2008
  5. Norman, Donald A. Design of Everyday Things, The. New York: Basic Books. 2002. (reprinted from the original, entitled, The Psychology of Everyday Things.)
  6. Основы бизнес-анализа : учебное пособие / В.И. Бариленко, В.В.Бердников, Р.П. Булыга [и др.]; под ред. В.И. Бариленко. — М. : КНОРУС, 2016. — 272 с.
  7. Паклин Н.Б. Орешков В.И. Бизнес-аналитика: от данных к знаниям / Н.Б. Паклин, В.И. Орешков. – Питер, 2013. – 706 с.