BI Tools for Business and Political Analysis

2025/2026

Учебный год

ENG

Обучение ведется на английском языке

3

Кредиты

Кто читает:

Департамент политологии и международных отношений

Статус:

Курс по выбору

Когда читается:

2-й курс, 2 модуль

Преподаватель

Снытко Александр Николаевич

Course Syllabus

Abstract

The course introduces social-science students to the basic principles of analytical thinking and applied data analytics—from formulating research questions and hypotheses to collecting, cleaning, visualizing, and interpreting data. The main focus is practical work in Yandex DataLens (creating interactive dashboards) and working with open data sources. The platform is not mandatory; students may complete assignments and the project in any BI system.

Learning Objectives

• The aim of the course is to introduce the basic principles of analytical thinking and applied data analytics

Expected Learning Outcomes

• • Understands the role of BI and data visualization in social sciences.
• • Formulates research questions and hypotheses.
• • Searches for and describe open datasets.
• • Performs data cleaning and calculations.
• • Builds visualizations and dashboards in BI platforms.
• • Formulates analytical conclusions.

Course Contents

• Introduction to BI
• Connections and Datasets
• Charts
• Basics of Data Visualization
• Maps in DataLens
• Parameters and Selectors
• Dashboards—Assembly and Optimization
• Data Storytelling
• Mini-Case / Independent Work
• Final Session & Project Presentations

Assessment Elements

• Homework and Practicums
  Small assignments after sessions (data analysis, BI visualizations)
• Activity in seminars and practicals
  Participation in discussions, BI work in class, visualization reviews
• Mini-project (dashboard + presentation)
  Individual or paired work with open data

Interim Assessment

• 2025/2026 2nd module
  Homework and Practicums - 60% - Mandatory; Activity in seminars and practicals - 40% - Mandatory; Mini-project (dashboard + presentation) - up to 20% - Optional. Final = (Homework × 0.6) + (Activity × 0.4) + (Project_Bonus × up to 0.2). If the project is not completed, the maximum grade from mandatory elements remains 10 points. Classes are held online. The first class is an introductory lecture. Subsequent classes include a brief theoretical introduction and practical work with a BI platform, as well as work on mini-projects.

Bibliography

Recommended Core Bibliography

• Hsinchun Chen, Chiang, R. H. L., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165–1188. https://doi.org/10.2307/41703503

Recommended Additional Bibliography

• Minelli, M., Chambers, M., & Dhiraj, A. (2013). Big Data, Big Analytics : Emerging Business Intelligence and Analytic Trends for Today’s Businesses. Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=518564