We use cookies in order to improve the quality and usability of the HSE website. More information about the use of cookies is available here, and the regulations on processing personal data can be found here. By continuing to use the site, you hereby confirm that you have been informed of the use of cookies by the HSE website and agree with our rules for processing personal data. You may disable cookies in your browser settings.

  • A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Visualization of business data on BI platforms

2024/2025
Academic Year
ENG
Instruction in English
3
ECTS credits
Delivered at:
Department of Business Informatics and Operations Management
Course type:
Compulsory course
When:
1 year, 4 module

Instructors


Замяткин Владислав Андреевич


Travin, Alexander

Course Syllabus

Abstract

The activity of any company implies the formation of a system of indicators of its work and their presentation in a visual and convenient for making managerial decisions. The aim of the course is to master the theoretical foundations and acquire practical skills in developing information and analytical dashboards. On the example of real cases the stages of creating such dashboards of different levels of complexity are considered: from the formation of requirements to their full technical implementation.
Learning Objectives

Learning Objectives

  • The aim of the course is to teach students modern methods and tools of data visualization using BI platforms. Throughout the course, students will learn the key stages of working with data, including data preparation, data modelling, data visualisation and building interactive dashboards. This will help develop the skills necessary for effective data presentation and data-driven management decision-making.
Expected Learning Outcomes

Expected Learning Outcomes

  • Knowledge of principles and methodologies of data preparation for analysis (cleansing, transformation, integration)
  • Knowledge of the basics of data modeling (Star and Snowflake schemas)
  • Ability to apply various techniques of data preparation using Power Query tool
  • Ability to create data models, set up links between tables
  • Ability to write simple expressions in DAX query language to calculate indicators
  • Knowledge of basic principles and stages of dashboard development
  • The ability to select and use appropriate types of visualisation in order to draw conclusions for making data-based managerial decisions
Course Contents

Course Contents

  • Building dashboards
  • Data vizualization
  • Data modeling
  • Data preparation
  • Course outline. Visualization of business data on BI platforms
Assessment Elements

Assessment Elements

  • non-blocking Class participation and assignment
  • non-blocking Final test
  • non-blocking Project
Interim Assessment

Interim Assessment

  • 2024/2025 4th module
    0.25 * Class participation and assignment + 0.25 * Final test + 0.5 * Project
Bibliography

Bibliography

Recommended Core Bibliography

  • Power BI: моделирование на экспертном уровне : построение оптимальных моделей данных с использованием Power BI, Бахши, С., 2022
  • Бахши, С. Power BI: моделирование на экспертном уровне / С. Бахши , перевод с английского А. Ю. Гинько. — Москва : ДМК Пресс, 2022. — 490 с. — ISBN 978-5-97060-906-4. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/314864 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.
  • Говори на языке диаграмм: Пособие по визуальным коммуникациям, Желязны, Д., 2009
  • Феррари, А. Подробное руководство по DAX / А. Феррари, М. Руссо , перевод с английского А. Ю. Гинько. — Москва : ДМК Пресс, 2021. — 776 с. — ISBN 978-5-97060-859-3. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/190738 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.

Recommended Additional Bibliography

  • Данные: визуализируй, расскажи, используй. Сторителлинг в аналитике, Нафлик, К.Н., 2020

Authors

  • Орлова Екатерина Дмитриевна