Data Science is everywhere
The 2nd International Data Science Conference combined state-of-the-art methods from academia with industry best practices.
From 22nd to 24th May 2019 representatives of the academic and industry world met for the 2nd International Data Science Conference at Salzburg University of Applied Sciences. The international experts discussed challenges and trends regarding data science in industry, research, education, and society.
The technological progress in IT and the resulting changes in the business and social environment (“digitalization”) have led to an increase of the amount of data. Several billion terabyte of data have been produced up until now, and the number is growing exponentially. “Data collection permeates all areas of our lives: from standard use cases such as the analysis of our shopping behaviour followed by purchase suggestions, up to competitive sports”, explains conference organizer Peter Haber, lecturer at the degree programme Information Technology & Systems Management, wo has initiated the conference together with Manfred Mayr and Thomas Lampoltshammer (Danube University Krems).
In many places, data mining and machine learning have become part of the occupational routine in order to generate value out of the flood of data. “The permeation in all areas was evident at the conference. The presented use cases ranged from market and trend analysis, the energy, health and sports sector to predictive maintenance in the industrial sector”, summarizes Manfred Mayr, co-organizer and academic programme director of the degree programme Business Informatics and Digital Transformation, the key areas of the conference.
Besides talks about state-of-the-art methods of data analytics by researchers from the international academic community, business experts gave insights into best practices and obstacles from the practice. The conference highlights:
- Artificial intelligence and machine learning gain in importance
More and more manufacturing companies place greater emphasis on machine learning, a form of artificial intelligence that enables systems to learn independently from data. They, for example, optimize their maintenance with this method. Monitors, among others, get equipped with intelligent sensors to collect data. For analysing the data, so-called predictive anticipation algorithms give information about the projected maintenance need. With this, a lot of money can be saved.
- Developing the business models of the future with blockchain technology
Bodo Hoppe, distinguished engineer at IBM Research & Development GmbH, explained in his keynote that the potential for new business model lies in the continuous monitoring of the production and supply chain. With “IBM© Food Trust” the software giant IBM has developed a new trust and transparency system for the food industry. Hoppe: “The solution is based on blockchain technology and grants authorised users immediate access to meaningful data of the food supply chain, from the farm via the stores to the end consumer.”
- Small Data: Solutions for SME
The 2nd International Data Science Conference showed possibilities for the optimization of business models especially for small and medium sized enterprises (SME). “Often they are lacking the special knowledge and the supposed data to evaluate the chances and risks for their own company”, knows conference organizer Peter Haber. “Recent improvements in the area of deep learning, however, provide solutions for these cases with only limited data available”, says David Anastasiu, assistant professor at the department of computer engineering at San José State University. Thus, SME could improve their business operations significantly.
Josef Waltl, Global Segment Lead at Amazon Web Services and alumnus of the degree programme Information Technology and Systems Management, presented, therefore, in his keynote a cloud based machine-learning system that could help companies with their use cases.
- Open data & scientific cooperations as chances for SME
Peter Parycek, head of the department for e-governance in economy and administration at Danube University Krems, wants to open the access to the data of the big players. SME could use these open data as a reference to generate transfer possibilities for their use cases. Experts, therefore, advice SME to invest in data scientists. Stefan Wegenkittl, academic programme director of the degree programme Applied Image & Signal Processing as well as head of the applied mathematics and data mining department at the degree programme Information Technology and Systems Management, emphasized the possibility to intensify the exchange with higher education institutions: “Suitable solutions can be found if agile development and management processes are connected with current data science research questions.”
- Social benefits: detecting autism & revealing insider trade
Data science offers exciting possibilities not only for business purposes. David Anastasiu from the San José University presented his research project about the computer-based detection of autism. Anastasiu and his team received the respective data from electrocardiograms, which measure the activity of all heart muscle fibres, and data about the skin conductance. With this information, they determined the course of the relaxation times which – as they could show in their research project – can give an indication about whether a person is suffering from autism or not. Anastasiu: “Our model reached an accuracy of 99.33 percent. Diagnosis by doctors are around 82.9 percent accurate.” Jad Rayes and Priya Mani from the George Mason University presented another field of application with social benefit. They are able to detect insider trade activities. With this information, the police could reduce the crime on the capital market.
Positive feedback for the conference
The high number of participants as well as their positive feedback proved that the concept of the conference is successful. “The participants liked the format as well as the size. The great mix of academic inputs and practical examples from the industry was appreciated”, so Haber proudly. The next conference will take place from 13th to 14th May 2020. “But this time in Dornbirn, in cooperation with FH Vorarlberg” – another indicator for the successful concept.
Data Science at Salzburg University of Applied Sciences
With a particular specialization in data science & analytics in the master’s programme, the degree programme Information Technology & Systems Management at Salzburg University of Applied Sciences offers prospective data scientists a perfect education. Alumni have, besides mathematical and statistical core competences, fundamental knowledge in the areas machine learning, data mining and deep learning.