Smartphones and other smart devices are now an integral part of our lives. Technological developments go hand in hand with our daily lives. For example, do you listen to your smart device telling you what to wear based on the weather forecast? According to scientists, there are countless such things that can be predicted on the basis of data, but is this really the case and are these predictions correct? You are listening to the beginning of a series of three podcasts on Data science with professors from Maastricht University and the Brightlands institute for smart society (BISS). Today we talk to Rudolf Müller.
Rudolf Müller is a professor of Quantitative Economics at Maastricht University and is affiliated with the BISS institute. His work at BISS focuses on designing smart service systems, aligning computational performance, user satisfaction and economic performance from a multidisciplinary perspective. Rudolf tells us about data science in general today. Next week's guest is Lisa Brüggen, who tells us about using data science and data science biases. Finally, we conclude this series with Gijs van Dijck who tells us about ethical and legal issues within data science and the social context.
Data science within digitization
Rudolf says, "There is a tremendous amount of data and a tremendous amount of access to data. We are actually now at a stage of digital development where we are building a complete digital twin of ourselves." According to Rudolf, by learning to build new forms of algorithms today, we can understand different aspects without needing specific knowledge. How can you do something with this as an entrepreneurial professional? You'll hear about it in this episode!
Is data science the future?
Digitization is new, but using data to make decisions is actually not new. Once it is clear what you want to achieve with collected data, as an entrepreneur you can possibly build algorithms and implement them in your business strategy. In this episode, Rudolf Müller answers questions such as: How far do we want data science to take us? What do we want to predict? And; how vulnerable is it really?
Links
All about the Brightlands institute for smart society (BISS)
More about the Working Professor
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