Big Data is a term that is everywhere these days. Across a range of disciplines, the ability to collect and process large sets of data has had great implications. In this public lecture, three Professors will discuss the phenomenon of Big Data from three different scientific perspectives:

Computer Science, Rasmus Pagh (ITU)
In his research he works on tackling the problem of creating algorithms that extract insights from very large data sets. The "scalability engineering" view of the challenges of handling big data is often presented as two of the “three Vs of big data”. But there are several other interesting problems around big data that deserve attention. Rasmus Pagh refers to some of these as the “three Ps of big data”. Complementing the other speakers’ thoughts about the Possibilities of big data, Rasmus Pagh will discuss some of the Pitfalls and Privacy concerns that arise.

Business, Roman Beck (ITU)
Roman Beck will talk about the increasing importance and challenges to deal with unstructured social media data and unstandardized financial reference data within the financial services sector which is a problem for commercial banks as well as financial regulatory authorities. The problem is amplifying because of the exponential increase of speed of the bank transaction systems while the backend processes could not keep up simultaneously. So more data of unknown quality and validity is flooding into the backend systems which are supposed to secure the stability and deal with financial risk management but are increasingly outpaced by the front end systems.

Science, Brian Vinter (KU)
The concept of Big Data has been reality in science long before the term was coined. In this talk Brian Vinter will introduce examples of Big Data applications in science, mostly physics, and show just how large datasets become in science these days, and how we are addressing these data, both algorithmically and technically.

The event is hosted by Anders Høeg Nissen of Harddisken DR P1.

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