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

26 Shabolovka st.
Phone/Fax: (495) 772-95-69
Email: management@hse.ru   

School Head Nikolay Filinov
Deputy Head Ulyana Podverbnykh
Deputy Head or work with graduates and interaction with business Ekaterina Valeryevna Buzulukova
HSE Lyceum Affairs Coordinator Nazar Tishchenko
Prospective Students and Students Coordinator  Milena Obushcharova
Manager of the School Project Office Daria Wijler
Crossing Borders in Gender and Culture

Prosvirkina E. Y., Bert W.

Cambridge Scholars Publishing, 2018.

Book chapter
Digital Transformation of Business Model of Russian Generating Companies

Maria Gorgisheli, Volkova I.

In bk.: ANNUAL GSOM EMERGING MARKETS CONFERENCE 2019. St. Petersburg: St. Petersburg State University Graduate School of Management, 2019. P. 60-62.

Working paper
Research of labor interests in the personnel management system

Lobanova Tatiana.

behavsci. ID: behavsci-657165. Behavioral Sciences Journal, 2019

Students of the Faculty of Business and Management Attended an Intensive Course on Business Intelligence

The course on the basics of data analysis from the teachers of Maastricht University,  specifically designed for the Master's students of the Faculty of Business and Management and postgraduate students of the Graduate School of Management, was held from November 20 to 24 at the Higher School of Economics.

The Business Intelligence course serves to develop skills in master and PhD students that are considered highly relevant for contemporaneous bussiness and academic practices. The quantitave analysis of large datasets by a variety of statistical and data mining techniques allows the students to gain marketing and managerial insights beyond that provided by textbook theory alone. While the course admittedly is quite short, preventing us from going into considerable detail, the material covered provides a thorough introduction to the field of data analytics and should provide students with the necessary tools to allow a continued development of individuals skills in the desired direction.

Furthermore, the R workshops introduce one of the most powerful and widely accepted programming languages in the statistics community. With the use of practical examples, interactive demonstrations, and an individual assignment in which students perform their own analysis of a real-life dataset, the workshops aim to provide sufficient knowledge to enable standard implementation of a selection of the most popular data analytical methods. As is usually the case when learning a programming language, the start is always the most difficult part. We hope that the workshops help the students across this initial hurdle and promote a longer-term use of this highly sophisticated program.

The program of the course included 6 lectures, where lecturers from Maastricht University Alexander Grigoriev and Etienne Wijler uncovered theoretical principles of methods, as well as 2 seminars were held. In the theoretical part of the course, emphasis was put on the use of data analysis methods in solving specific business problems, which makes it possible to create a more complete picture of the fields of application of the acquired knowledge. The practical part was aimed at developing the students' skills in applying the algorithms to real-life problems with the use of R.

According to the participants, the acquired knowledge from the Business Intelligence course is useful not only in scientific research, but also in decision-making in applied projects in the field of marketing and management. Now the students carry out the final task to analyze the data, we wish them good luck for successfully completing the course!


Visiting lecturers:

Alexander Grigoriev, Associate Professor, Maastricht University, PhD; Professor, Novosibirsk State University.

Almost 20 years (since 1999) Alexander (or Alex, as he asked students to contact him) is working at the University of Maastricht in the Department of Quantitative Economics in the direction of Operations Research.

The main areas of interest: operations research, combinatorial optimization, business intelligence. At the University, he teaches courses on Algorithms and Optimization (MSc Econometrics & OR), Business Analysis (MSc Business Intelligence), Operations Management (3rd year BSc International Business),Management of Operations and Product Development (2nd year BSc International Business). In 2017 he opened a program MSc Business Intelligence and Smart Services.

Etienne Wijler, PhD in Econometrics, Maastricht University. Etienne works at the University of Maastricht in the Department of Quantitative Economics in the direction of econometrics. Etienne spends most of his time researching the forecasting performance and inferential theory of high-dimentional time series methods such as the LASSO. At the University of Maastricht, he leads courses in Statistics for social sciences, Quantitative Methods for International Business students and Mathematical Statistics to Econometrics students. 

'The experience at HSE has been very positive. Many students have enthusiastically completed the entrance exam with great success. The workshops were characterized by two-way communication between the students and me, and I was genuinely impressed by the ability of students to extend dry theory to managerial and marketing applications. While the learning experience is still ongoing by means of the individual assignment, based on the feedback of some students I am convinced that the course has already contributed to a better understanding of data analytics and R. I truly hope the students may find use of this the course during their future career, whether by data driven strategic decision making for a company, development of novel quantitative research ideas, or by any other means. Thank you for the warm welcome in the lovely Moscow and all the best to students and staff of the HSE.' 

Course organizers:

Olga Tretyak Head of the Department of Strategic Marketing, Professor

Daria Lagutaeva Senior Lecturer at the Department of Strategic Marketing. 

Daria Lagutaeva has commented on the course:

'Thank you to the course teachers, for the opportunity to learn the level of research in European TOP universities, for an excursion into the methods of data analysis, for the plain language and practical examples in which you can use the demonstrated tools. After the course, we organized an informal event in a bar near the main building of the Higher School of Economics. This format is especially useful when the course is given in a foreign language. Many students shared their impressions of the course, asked for teachers' advice and consulted about the study. I am pleased with the activity and interest of students in the subject of the course and their motivation to continue learning in this direction. It is too early to talk about the results of the course, but it will be possible to draw definitive conclusions after the students completed the final project.'

Some participants have also shared their impressions of the Business Intelligence course.

Kasenkov A. Master's Programme in Marketing, 1 year:

'What are my first thoughts after completion of the course? The course was very motivating. To master the basics of a completely new direction in such a short time is a great challenge for yourself. The course helped me to form a general idea of the modern methods of data analysis, which would be difficult to attain if I would have to study this field by myself. Possible, someone may even consider this course in deciding upon the direction of their professional development. I recommend the Business Intelligence course for those who have a limited understanding of machine learning, in-depth data analysis, and of the opportunities that these methods offer and wish to fill this gap. This is an up-to-date discipline, the tools of which can be successfully used in writing research papers. I hope that this project will be further developed and may even become a full course in our program. 
I understand how difficult it is to organize a course with invited foreign speakers... Still, since there were quite many first-year masters among the audience, it would be better to study Business Intelligence in the second semester, when most students followed econometrics (or refreshed statistics). An alternative may be to include an econometrics test in the entrance examination, even if it is something elementary. Just to understand the basic principles, like standard regressions for example. Perhaps, cases from business can further aid in learning the new material. There were examples about merchandising, product recommendations and consumer segmentation, but some of them were rather obvious and more complicated applications may be helpful.'

Murysev A., Master's Programme in Marketing, 1 year:

'I strongly recommend that anyone who did not dare to choose this course, to change their decision for next year as this course will really allow you to look at the data differently. Uncertainty will no longer be an obstacle on your path, and statistics will become your friend. All thanks to the wonderful teachers who are able to present the material cool and unconventionally. After having mastered the course, you will be able to work with the data. And to take objective, weighted decisions on their basis. In short: I recommend.'

Afanasiev Y., Postgraduate Student of the Graduate School of Management, 1st year of study

'Many thanks for the course of BI. The lectures and seminars were interesting and informative. The material shown can be used in our own scientific research. I have previously studied C and Pascal for half a year, and this short course in R allowed me to refresh and update my acquired knowledge. Many thanks to Alex and Etienne.'

Nedelko A., Postgraduate Student of the Graduate School of Management, 1st year of study

'For me, the course "Business Intelligence" represents basic knowledge and skills with which you can solve almost any problem in business or academic research. I am sure that the information received during this course will serve as the foundation for my further development in the field of data analysis. Thank you very much to the teachers, Alexander and Etienne, for such useful and, most importantly, applied material and for explaing the complex in a simple manner! I would also like to thank Daria for organizing this course.'

Anonymous review:

'Daria, Alexander, Etienne, thank you very much for this course! There is still a lot to learn but you gave us a great start!'