Инструменты BI для бизнеса и социального анализа

2026/2027

Статус: Маго-лего

Кто читает: Департамент социологии

Где читается: Санкт-Петербургская школа социальных наук

Охват аудитории: для своего кампуса

Преподаватели: Морева Юлия Евгеньевна

Язык: русский

Кредиты: 3

Контактные часы: 24

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Аннотация

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.

Цель освоения дисциплины

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

Планируемые результаты обучения

• 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.

Содержание учебной дисциплины

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

Элементы контроля

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

Промежуточная аттестация

2026/2027 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.

Список литературы

Авторы

Морева Юлия Евгеньевна

Программа дисциплины