4/2015, In English, Tutkimus ja innovaatiot

Big Data Analytics, a research project in the complex digital era

General

The security and stability in the digital economy has to be ascertained to ensure a competitive future for the Finnish business environment, using (Big) data and facts. The goal of this project is to make the “digital Finland” safe and to help decision makers to make good calls based on solid facts in order to safeguard the success in Finnish organizations. This project answers the call for relevant and top-level research efforts. The project aims at solving problems in several focus areas of the current challenges in Finland and the European Union. Project partners are Arcada University of Applied Sciences, Haaga-Helia University of Applied Sciences, Novia University of Applied Sciences.

Main Activities

There have been two parallel tracks of activities, both supporting each other and the common goal, i.e. teaching businesses and master students to make fact based decisions (topic 1) and Improving stability and security in the digital economy of Finland (topic 2). Whereas the first topic is very much focused on improving the relevance in education in Big Data and creating the foundation for understanding Big Data in real life as well as collaboration between industry partners and academia, the second topic is focusing on solving research problems and establishing a solid academic network.

In the first topic, workshops have been held between several companies and the academic partners. Also a popular seminar was held in the beginning of May 2014 in Haaga-Helia. The potential of Big data applications has been studied in three focused sectors: in the retail, financial and industrial sector. Knowledge transfer has been done (not only through workshops and seminars) but also through direct placement of a teacher in one of the partner companies; the focus has been put on ensuring relevance in the project through proper industrial collaboration.

In the second topic, there has been plenty of activities, i.e. a network with Goethe University has been established (with a visiting researcher there from Arcada). Also the collaboration with Open University (England) has continued as planned. The main outcome of financial stability research is found in the use of analytical techniques in systemic risk measurement, as well as a deeper understanding of the mechanisms behind financial instability, and finally in overall extension of analytical techniques in high level publication outlets (e.g. Quantitative Finance, Knowledge and Information Systems, Information Visualization, Quality & Quantity, Ecological Informatics etc).

The response have been positive also from the practitioners side from the project and a further understanding of the financial crises as well as a set of additional tools have been very welcomed. In addition, Arcada has hosted a conference in Systemic Risk Analytics, in cooperation with the Bank of Finland and the ESRB (European Systemic Risk Board) during the fall 2015 (for more info see http://risklab.fi/events/sra2015/). In our work concerning information security, the results has been in the form of new Hadoop implementations in intrusion detection applications as well as basic methods in machine learning aiding in information security efforts. The progress in text summarization research has been interesting, and the use of term weighting and text analysis methods in social media content analysis for image labeling has been explored. We have proposed a new approach of web content classification that combines topic extraction with sentiment analysis methods, and developed different classification models. In addition, we developed several versions of text analysis and feature extraction tools for the applications.

Outcomes

In Arcada, the outcome of the project (still not finished) has been contributions to a large number of publications (38) of which approx. half are in JUFO (Julkaisufoorumi) ranked forums (for more info see http://www.arcada.fi/sv/forskning/forskningsprojekt/big-data-analytics). Additional research projects have been obtained in conjunction to this project. The impact of these results may be found in better understanding of financial stability processes, big data potential in information security issues and the potential of big data applications in the retail sector, industrial sector and financial sector. Also novel methods in the field of Machine learning have been obtained, on which future application in the industrial sector can be created.

Closing remark

This project has definitely helped research in Big Data Analytics to be placed not only in the traditional universities, but also in universities of applied sciences. The research activities in this area have, through the project, gained visibility and a solid network of academic and industrial partners. In the research field, we have obtained many results already in terms of publications and projects and we foresee no problem in achieving the desired research results from this project by the beginning of 2016.

Author

Kaj-Mikael Björk, Head of Department, Dr. Econ, Dr.Tech, Arcada University of Applied Sciences, Department of Business Management and Analytics, bjorkpau@arcada.fi

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