Магистратура
2023/2024
Аналитические системы финансового менеджмента
Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Статус:
Курс по выбору (Финансы)
Направление:
38.04.08. Финансы и кредит
Кто читает:
Департамент финансов
Где читается:
Санкт-Петербургская школа экономики и менеджмента
Когда читается:
2-й курс, 1 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для всех кампусов НИУ ВШЭ
Прогр. обучения:
Финансы
Язык:
английский
Кредиты:
3
Контактные часы:
28
Course Syllabus
Abstract
The course aims to equip students with conceptual knowledge, strategic analytical skills and modelling methods for efficient implementation of enterprise performance management system and Management by Objectives with focus on value creation and economic efficiency. During the study students will learn and practice instruments that are used in linking strategic goals with the operational activity to achieve profitability and economic growth of the company that operates in modern global market. Cross-disciplinary approach combines conceptual elements of business-modelling, strategy & marketing, enterprise architecture, business analysis and managerial accounting that will lead students through different levels of decision-making in decentralized company to understanding and ability to construct a complex financial model that serves value creation process.
Learning Objectives
- To develop knowledge of analytical tools used in financial management.
- To develop skills in analyzing financial data.
- To develop understanding the principles of data modeling, key principles of data preparation and data analysis.
- To get skills of working with BI systems and SQL.
Expected Learning Outcomes
- the knowledge of analytical tools used in financial management
- skills in analyzing financial data
- understanding the principles of data modeling
- key principles of data preparation
- key principles of data analysis
- skills of working with BI systems and SQL
Course Contents
- Financial information systems
- Data sources for financial analysis Data quality, Data engineering.
- Data modelling
- SQL for analyses finance data
- Visualization of financial data.
- Project defense
