A New Discipline Is Born: Processing Super-size Data
Will van der Aalst and Laboratory of Process Aware Information Systems staff
What influence does big data have on today’s world? What is a ‘data scientist’ and what skills does one need? Those were the subjects of a lecture at HSE by HSE honorary professor Will van der Aalst, from Eindhoven Technical University (Netherlands).
Professor Will van der Aalst has a longstanding history of working with HSE, and was involved in creating the Laboratory of Process-Aware Information Systems (PAIS Lab) MA programme, which he supervised until 2014. In addition to heading the IEEE Task Force on Process Mining, which includes over 50 universities, research centers and IT companies, Professor van der Aalst collaborates on integrating research at HSE and global research networks. He is currently involved in joint research projects and preparing findings for publication with colleagues from HSE.
Professor Will van der Aalst is one of the leading specialists in the modeling and analysis of information systems. He is also the creator and leader of a new, in recent years fast-growing, discipline – process mining. His ideas have had a great impact on researchers and programmers.
What is big data? What role does it play in today’s world?
In just a matter of a few years our society has moved from analogue to a fully digital existence. 10-20 years ago computers were still viewed as specialist machines only available to professionals. Now we all use a smartphone or a tablet, pay for purchases by card, order tickets over the internet and so on.
These significant technological breakthroughs had an astonishing impact on science, business, and daily life. All the information systems we have today are constantly producing massive volumes of data: big data. Everything everywhere is recorded all the time. Transport companies, insurance companies, banks and other businesses base their operations on process oriented information systems. Every one of us, when we buy coffee, send an email, have a phone call, or fill our cars, are involved in a massive data collection exercise. The things around us also produce data: just the iPhone alone contains over 14 sensors for receiving and processing information. Every year data gets bigger and bigger, and the volume increases in line with Moore’s law for transistors. Their overall volume on average doubles every two years. Although the technology for data storage and processing has made great strides forward since the 1960s, they cannot keep up with the pace at which data size and volume is growing.
It is becoming clear that a whole new discipline is emerging – processing supersize volumes of data. As in computer sciences, which grew from applied and fundamental mathematics as computers were developed, data science is developing rapidly, and there is a plethora of data to study.
Researchers world over face the task of effectively using the massive volumes of data available. This could, potentially, make commercial and state companies more efficient in their operations and improve daily life for all of us.
A profession that’s guaranteed to be ‘in demand’
If we are to deal with these data analysis issues, then universities must train people in fundamentally new programmes. That is why this composite profession of ‘data researcher’ has emerged globally.
Data scientists must have new skills and knowledge drawn from several different areas: computer sciences and programming, mathematical methods, and also business administration and management. These composite professions will always be in high demand, but also difficult to master. Key data analysis methods include computer-aided learning, data mining, process mining, visual analytics, time series analysis, and others.
Thus, data science is filling the gap between classical mathematics and applied computer sciences. Today, data scientists face numerous open questions. Some have been around for a while, but others have only just recently emerged. They include:
- How can we analyse data in real time without interrupting the process?
- How can we avoid clear and hidden discrimination in data analysis?
- How can we answer questions that haven’t been asked yet?
- How can we solve data analysis issues while keeping data private?
- Who makes the final decisions: what role does the expert play?
- What is the impact of correlation and cause-effect connections?
These questions are still waiting for scientists to start investigating them.
Graduate students and students should think about whether they might enjoy a career in data analysis, which is sure to be in demand for the next 10 – 20 years. Data scientists, in the near information future, will occupy a similar position to other professionals we see today, such as programmers and information systems architects.
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Nikita Kazeev holds a Candidate of Sciences degree (Russian equivalent of a PhD) in Computer Science and a PhD in Physics. He is a Research Fellow at the LAMBDA Laboratory and works at CERN. In an interview with HSE News Service, he talked about what it was like to defend his dissertation in a double doctoral degree programme at HSE University and Sapienza University of Rome, what it is like to conduct research in Geneva, and why it is imperative to communicate with colleagues.
Ismail Kayali, from Aleppo, Syria, earned his MS in Big Data Systems from the HSE Faculty of Business and Management in 2018. He is currently pursuing a PhD in Informatics and Computer Engineering at the HSE School of Data Analysis and Artificial Intelligence.
Sangam Kumar Singh is currently finishing the second year of his Master of Science in Big Data Systems. After spending the first year at HSE Moscow, he has gone to the UK on a double degree track with Lancaster University. Sangam has talked to HSE News Service about his studies, hobbies, research interests, and future plans.
During the XX April International Academic Conference on Economic and Social Development, scheduled this year for April 9-12 at the Higher School of Economics, Dr David Garcia of the Complexity Science Hub Vienna and the Medical University of Vienna, Austria will present a report entitled ‘The digital traces of collective emotion’ at a session on ‘The Wellbeing of Children and Youth in the Digital Age.’ Ahead of the conference, Dr Garcia spoke with the HSE News Service about his conference presentation, his research, and plans for ongoing collaboration with HSE colleagues.
Sangam Kumar Singh has come from India to do a Master’s in Big Data Systems at the HSE School of Business Informatics in Moscow. He has chosen HSE due to its high standing in global university rankings such as QS and the Times Higher Education ranking as well as its focus on research and innovation. Having started his career in engineering within telecommunication business and later moving onto R&D application and analytics in the same area, he was drawn to HSE’s programme because it combines business, informatics and analytics and equips its graduates with the skills and knowledge required by our modern economy and ever-changing market dynamics.
On June 29, the third graduation ceremony for the double-degree Master’s programme in Big Data Systems (HSE, Russia) and Information Systems Management (UAS Technikum Wien, Austria) was hosted at the Austrian Ambassador’s Residence in Moscow. Dr. Hartmut Koller-Lenhardt, Chancellor at the Embassy of Austria in Moscow, gave the opening address. He congratulated the graduates on their successful completion of the programme and stressed the importance of cooperation between the universities in regards to cultural and professional communication and connections.
Fedor Ratnikov, a leading researcher at the Laboratory of Methods for Big Data Analysis (LAMBDA), has been appointed project coordinator in the SHiP collaboration. He will be responsible for developing and designing the detector’s active magnetic radiation shielding.
HSE will launch a new project called Data Culture in September 2017. Starting their very first year, HSE bachelor’s students will learn to work with data, and students in a number of programmes will also become familiarised with methods of machine-learning and artificial intelligence.
First Graduates Complete Double-degree Master’s Programme in Big Data Systems and Information Systems Management
On June 27, 2016, the first graduation ceremony for the double-degree Master’s programme in Big Data Systems and Information Systems Management was held at the Higher School of Economics in Moscow. The ceremony marks three years of successful collaboration between HSE and University of Applied Sciences Technikum Wien.
The Master’s programme in Big Data Systems at the Higher School of Economics focuses on the value aspect of big data for large enterprises and the implementation of big data technology in enterprises. Two current students of the programme share their thoughts about what drew them to HSE to study big data, what they hope to gain from the programme and what advice they would give to prospective international students.