How did the term 'big data' come about? What difficulties might students encounter when mastering the profession of business analyst? Where and how to look for a job in this field? These and many other questions were answered by: Tatiana Gavrilova, Academic Director of the Master in Business Analytics and Big Data (MiBA) programme and Head of the Department of Information Technology in Management at the Graduate School of Management at St Petersburg University, and her colleague, Vasilii Garshin, Advisor to VTB Bank and curator of the MiBA transformation project.
Photograph: Tatiana Gavrilova
Ms Gavrilova, what are the benefits of a degree in big data analytics?
Tatiana Gavrilova: Higher education in the field of big data probably does not offer any extraordinary advantages, but it provides an opportunity to acquire interdisciplinary knowledge. There are people with a synthetic mind who are interested in being on the cutting edge of technology and use everything that modern science produces in their work. We would like such people to have an education that would enable them to work at a professional level.
Today, we are introducing a new subject area – data analysis, a field which has long been neglected in our country. Data-based decision-making has become a clear global business trend. This is not a purely theoretical or subjective approach, but a way to: compare what has been done before with what will be done in the future; analyse the reality; and then make decisions based on this analysis. This approach will enable our students to work in many fields – biology, biochemistry, production management, design agencies, and many other areas. This is our main advantage, because big data analysis is now everywhere.
How did this trend emerge? When did people decide to stop pluck figures out of the air, as it were?
Tatiana Gavrilova: This process is closely related to technological revolutions: discussions about the increasing flow of information began when computers were first introduced, but the trend has become particularly relevant now. Today, almost everything is digitised. People use multichannel means of communication and always carry their gadgets. This data must also be analysed, interpreted and put to work. Although there has always been a lot of data, now there is a huge amount of it and people are no longer able to process it manually. That is why information technology (IT), which spawned this 'big data' monster, has come to our aid and helped us learn how to deal with it. This is how the profession of a big data analyst came about. Then it became clear that not only an analyst is needed, but also a manager, and so the professions of knowledge-analyst and knowledge-manager emerged. We have observed a particular interest to this area in the last decade.
Vasilii Garshin: I would like to point out that when all of a sudden we started making decisions based on data alone, the leap was not so dramatic. Technology has developed gradually, together with computers and processes. During the course, we want to show students this evolutionary path, not just train specialists in a popular profession. Very often there is a feeling that a data-scientist who comes to an organisation will solve a lot of problems, leaving behind everything that has been done before. Our goal is to train people with a broader perspective, who are able to look at a situation from a wider angle as a result of their more advanced outlook. This is what we see as the main benefit of the programme.
What other skills will distinguish the graduates in this high-street field?
Tatiana Gavrilova: Such popularity stems from the fact that the market, as always, has great expectations, including for data-scientists. This is indeed a very dynamic field, which can be called a 'bandwagon', meaning that it is heading in the right direction. In my personal life, I have already seen several bandwagons, with artificial intelligence being the last that everyone tried to jump on. Our graduates will become proficient in intellectual technology, because we include all of its major sections in our courses: natural language processing; machine vision and learning; and neural network training. Since this is a global trend, it cannot be ignored, because the whole world is moving towards intellectualisation.
It seems to me that our graduates will be more prepared for real work, as we provide hands-on training, with data coming from real companies. Even the defence of their graduation projects is organised in the form of pair work. The time for loners is gone; no task can be solved by one person, be it the most ingenious employee. They will never be put in a situation where they will hear: 'Now, forget everything you've learned and studied. Here comes the real life'. With English as a language of instruction, their main advantages will include broader outlook, internationalisation and readiness for practical work.
Can self-taught people, who have not got academic education but have taken online courses, for example, succeed in this field?
Tatiana Gavrilova: This is an interesting question. Given that the profession of analyst has many gradations (on one side of this scale there is business and on the other side there is machine learning), the education process for self-taught people tend to be closer to machine learning. This kind of learning has its advantages, but is very spot-on: it is like a trip to a fair, where you can pick up a bag of goods from all different stalls that you like. An alternative to it is to go shopping with a shopping assistant, who tells and shows you the best bargains and the best quality. They also point the way to stalls that you might otherwise overlook, where you can find more interesting and useful things. This is an allusion to the academic form of learning. Learning without a teacher is always longer, because experience saves a lot of time and also helps to build a structured system of knowledge in the student's mind.
How often do students get the chance to talk personally to people who have achieved success in this field?
Tatiana Gavrilova: It happens regularly. Every Thursday, business experts deliver a lecture and talk to the students to share their best practices. These experts include specialists from VTB Bank, Gazprom, Severstal, and many other companies. All of them are very enthusiastic about making contact with students. Moreover, each course is taught by two professors – a practitioner and a faculty member from the Graduate School of Management. Our students are never short of opportunities for communication and consultation.
Are graduates seeking employment in private companies or in state-owned enterprises?
The Graduate School of Management has a Career Centre which helps students make their choice. However, many graduates get a job offer while they are still working on their graduation projects. Big data comes both from large corporations and small IT companies that are often involved in studying data from major enterprises. IT companies are a whole new planet with an atmosphere of their own. Right now, they seem to be one of the most exciting market participants.
Vasilii Garshin: I would like to note that, according to various economic estimates, the public sector has a significant share of the Russian economy, so it is necessary to target both the largest state-owned corporations and public companies as potential employers. It doesn't really matter whether graduates choose private business or a state enterprise. They will do well in all of them. I might also note that it is virtually impossible to learn the entire managerial business on your own. This is where our strengths are most obvious: we can provide students with the opportunity to learn about the whole system, rather than just a particular skill.
Do companies give assignments to students during their studies?
Tatiana Gavrilova: In management, this is called a 'case championship' – a competition organised by companies and consisting of tasks directly related to practical work. It is true that large corporations are not always willing to share their data with a large circle of people, so students often sign non-disclosure agreements. However, this gives them the opportunity to use real data for their graduation projects.
Vasilii Garshin: During their studies, students build up a personal portfolio, so they will not leave the University empty-handed.
What advice would you give to those who are just thinking about becoming a business analyst?
Tatiana Gavrilova: I would advise them to become a frequent visitor to the library, even to a virtual one. They have to read a lot and broaden their horizons. Students also need to communicate more with each other. Mutual support is important, because these people will become part of your professional community in the future.