• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • А
  • А
  • А
  • А
  • А
Обычная версия сайта

Summary of Degree Programme

Field of Studies

38.04.05 Business Informatics

Approved by
Directive on Programme Approval № 6.18.1-01/1508-10 of 15.08.2014
Last Update
Approved by the Academic Council of the Programme, minutes meeting № 1, dated 05.11.2018
Network Programme

No

Length of Studies, Mode of Studies, Credit Load

2 years

Full-time, 120

Language of Instruction

ENG

Instruction in English

Track(s)
None
Degree Level

Master

Double-degree Programme

Yes

Competitive Advantages

The term "BigData", which has arisen in the last decade, is directly related to the emergence of the problem of a rapid increase in the volume of data that occurs, first of all, in business structures due to the fully functional informatization of business processes; in scientific organizations - due to the emergence of new measurement opportunities; in government organizations - with an increase in the volume and functionality of services, as well as in public communication networks.

An important feature of the program is its focus on the needs of the business in new technology. The program focuses on the enterprise, as on a system with a developed information infrastructure that provides automation of management tasks. In this aspect, it becomes possible to distinguish classes of managerial functions, where the introduction of big data technologies will make it possible to obtain new characteristics of activity for making decisions, forecasting and forming control actions. The “from tasks to technology” approach incorporated into the program develops competencies that are important for specialists who can accelerate the implementation of big data technology in practice, and will ensure high demand for both the technology itself and the existing tools.

Professional Activities and Competencies of Programme Graduates

The program is aimed at the formation of the following interdisciplinary competencies:

  • mathematical and technological knowledge and skills for the selection, assessment, analysis and use of tools and big data technologies;
  • competencies providing an understanding of business architecture, the impact of introducing new IT technologies, including big data technologies, on the efficiency of enterprise management, changing the value chain;
  • management competencies in the implementation of big data systems and services based on big data technologies;
  • research competencies in the field of big data analytics, stochastic optimization, predictive modeling, forecasting, enterprise data management, business analysis, economic and mathematical modeling.

The program is focused on training graduates who are able to:

  • carry out work on the implementation and evaluation of the effectiveness of technologies and tools of big data at the enterprise;
  • manage enterprise data (Data Management);
  • introduce and apply analytics and decision support tools based on big data technologies, implement decision management (Decision Management);
  • to develop new models of enterprise information infrastructure, taking into account the capabilities of big data technologies (Model Management).
Programme Modules

The program consists of compulsory disciplines, varied disciplines, term paper (first year of study), a scientific seminar and a master's thesis (second year of study).

Mandatory disciplines

  1. System Analysis&Organization Design (Системный анализ и организационный дизайн)  
  2. Economic and Mathematic Modeling (Экономико-математическое моделирование)
  3. Enterprise Architecture Modeling (Моделирование архитектуры предприятия)
  4. Advanced Data Analysis&Big Data for Business Intelligence (Перспективные методы анализа данных и Большие данные в бизнес-интеллекте)
  5. Big Data Systems Development and Implementation (Pазработка и внедрение систем больших данных)

Variable Modules

Technological unit

  • Data Visualization (Визуализация данных)
  • Predictive Modeling (Предсказательное моделирование)
  • Natural Language Processing and Cognitive Modelling (Обработка естественного языка и когнитивное моделирование)
  • Cloud Computing (Облачные вычисления)
  • Big Data Collection, Storage&Processing in Heterogeneous Distributed Computer Networks  (Сбор, хранение и обработка данных в гетерогенных распределенных компьютерных сетях) 
  •  Knowledge Discovery in Data at Scale Technologies (Технологии извлечения знаний из большого объема данных)
  • Applied  Machine Learning (Прикладные аспекты машинного обучения)

Management unit

  • Creating and Managing Enterprise  Information Assets  (Создание и управление информационными активами предприятия )
  • Advanced Data Management (Современный менеджмент данных)
  • Big Data Based  Marketing Analytics (Маркетинговая аналитика на основе больших данных)
  • Big Data Based  Risk Analytics (Анализ рисков  на основе больших данных)
  • Process Mining and Big Data Driving Process Management (Анализ процессов и управление процессами на основе больших данных)
  • Big Data Analytics for Industrial Internet (Аналитика больших данных в индустриальном интернете)

The student can choose disciplines from both blocks in accordance with individual input competencies and focusing on the prerequisites indicated in the course program, as well as courses from other master's programs (in English).

Adaptation courses

  • Enterprise Architecture (Архитектура предприятия)
  • Data Analysis (Анализ данных)

Term paper

The research seminar is focused on the study of the areas of application of big data technologies, the study of practical work with big data tools, as well as on the analysis of the development of this technology

Options for Students with Disabilities

This degree programme of HSE University is adapted for students with special educational needs (SEN) and disabilities. Special assistive technology and teaching aids are used for collective and individual learning of students with SEN and disabilities. The specific adaptive features of the programme are listed in each subject's full syllabus and are available to students through the online Learning Management System.

Programme Documentation

All documents of the degree programme are stored electronically on this website. Curricula, calendar plans, and syllabi are developed and approved electronically in corporate information systems. Their current versions are automatically published on the website of the degree programme. Up-to-date teaching and learning guides, assessment tools, and other relevant documents are stored on the website of the degree programme in accordance with the local regulatory acts of HSE University.

I hereby confirm that the degree programme documents posted on this website are fully up-to-date.

Vice Rector Sergey Yu. Roshchin

Summary of Degree Programme 'Big Data Systems'

Go to Programme Contents and Structure