Кузнецова Анастасия Дмитриевна
Мусабиров Илья Леонидович
- introduce the basics of human visual perceptions, choice of appropriate graphics, its design and storytelling with data
- be able to find appropriate graphics for their data
- be able to communicate data from the research efficiently
- be able to choose colors and shapes of visualization more efficiently
- have knowledge of where it is possible to produce different types of diagrams
- have skills of data visualizations in the main tools and software (Tableau, Excel, online tools)
- be familiar with the basics of data storytelling
- Principles of data visualization1) Basics of data visualization and visual perception. History of data visualization and key figures. Main concepts of visual perception of graphics. 2) Getting started with Tableau Overview of the Tableau interface. How to make bar charts, scatter plots and line graphs. Data aggregation and data filtering with continuous, categorical and time data.
- Visualization for business analysis3) Information Dashboards Design Main rules for making efficient dashboards. What is KPI and how to make them in Tableau. The use of calculated fields for data analysis in Tableau. 4) Dashboards in Data Studio Connection to data sources and making real-time dashboards in online tool Google Data Studio.
- Improving graphics and unusual diagrams5) Choosing the best graphics for your data Overview of data types and diagrams for efficient data communication. How to make highlights at the diagrams. 6) Practising different types of diagrams Working with different types of diagrams and their use for data analysis. A Proper explanation of statistical diagrams - box plots and correlation plots. 7) Maps and networks Desktop and online tools for making maps. Basics of work with Russian geodata. Basics of Gephi. An overview of online tools for visualizing networks. 8) Data storytelling Making an efficient presentation with data storyline. Basics of infographics. 9) Project presentations Final presentations of group projects.
- Interim assessment (3 module)0.45 * 3 homework assignments + 0.35 * Final group project + 0.2 * In-class written assignments (test)
- Knaflic, C. N. (2015). Storytelling with Data : A Data Visualization Guide for Business Professionals. Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1079665
- Monsey, M., & Sochan, P. (2016). Tableau For Dummies. Hoboken, NJ: For Dummies. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1082334
- Acharya, S., & Chellappan, S. (2017). Pro Tableau : A Step-by-Step Guide. New York: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1403967
- Rahlf, T. (2017). Data Visualisation with R : 100 Examples. Cham, Switzerland: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1377904
- Schrödinger, E., & Niall, K. K. (2017). Erwin Schrödinger’s Color Theory : Translated with Modern Commentary. Cham, Switzerland: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1651581