Programme

When do we reach value out of our data efforts? How do we move an organisation towards this new way of working? How can we become really customer centric? Telenet Business found his way in this challenge and will give you some interesting insights on the key principles for success, how to set up the right organisational format, the different data capabilities they put focus on and the way of implementing those projects. Lieven Foubert will bring a specific example of a case with a start-up.

In order to overcome various data challenges, the Borealis data & analytics team decided to invest in a Data Lake. With this lake Borealis, a leading provider of innovative solutions in the fields of polyolefins, base chemicals and fertilizers, wants to:

– reduce data preparation time for data science work;
– be able to deal with the evolving data scope, growing volume and increasing complexity
– build something that power users can develop, operate and leverage themselves

In this keynote Nathalie Rigouts, Head of IT Innovation of Borealis will share the current status and lessons learned on this agile way of working to incrementally develop a solution for data challenges in an interactive way, driven by business needs. Nathalie will also explain why having a data lake will not solve all issues and will highlight how to handle data governance.

Data science ethics is about deciding what is right and wrong in data science. Based on several cautionary tales and concepts, Professor David Martens will demonstrate the importance of considering data science ethics for businesses, both in terms of potential risks, as well as the value it can deliver. This ranges from being able to explain predictions like in the recent Apple Card case and learning from wrong patterns in radiology, to detecting discrimination against sensitive groups like Amazon recruitment system discriminating against women and the US recidivism prediction system discriminating against black persons. Professor David Martens will also share his insights on the use of data as a weapon against pandemic.

VRT is built on strong brands. In Mass media these brands are built on relations. Research and data has been the base to understand citizens and act as great companions. In an international competitive environment, how can local media-companies demonstrate their value? And how can we keep track of the diverging media use of our services? It is in VRT’s vision to help creating new measurement systems within an innovative data-approach. Collaboration with other (media)-companies will be key for success. Our ambitions are to collect and connect user data, demonstrate value and to develop analytic and predictive models.

In order to overcome various data challenges, the Borealis data & analytics team decided to invest in a Data Lake. With this lake Borealis, a leading provider of innovative solutions in the fields of polyolefins, base chemicals and fertilizers, wants to:

– reduce data preparation time for data science work;
– be able to deal with the evolving data scope, growing volume and increasing complexity
– build something that power users can develop, operate and leverage themselves

In this keynote Nathalie Rigouts, Head of IT Innovation of Borealis will share the current status and lessons learned on this agile way of working to incrementally develop a solution for data challenges in an interactive way, driven by business needs. Nathalie will also explain why having a data lake will not solve all issues and will highlight how to handle data governance.

VRT is built on strong brands. In Mass media these brands are built on relations. Research and data has been the base to understand citizens and act as great companions. In an international competitive environment, how can local media-companies demonstrate their value? And how can we keep track of the diverging media use of our services? It is in VRT’s vision to help creating new measurement systems within an innovative data-approach. Collaboration with other (media)-companies will be key for success. Our ambitions are to collect and connect user data, demonstrate value and to develop analytic and predictive models.

Data science ethics is about deciding what is right and wrong in data science. Based on several cautionary tales and concepts, Professor David Martens will demonstrate the importance of considering data science ethics for businesses, both in terms of potential risks, as well as the value it can deliver. This ranges from being able to explain predictions like in the recent Apple Card case and learning from wrong patterns in radiology, to detecting discrimination against sensitive groups like Amazon recruitment system discriminating against women and the US recidivism prediction system discriminating against black persons. Professor David Martens will also share his insights on the use of data as a weapon against pandemic.