Dr. Brian MacNamee (DIT) talks about CeADAR and data analytics

so I'm Brian McNamee I'm from the Dublin Institute of Technology and I'm the the lead p.i on the intelligent analytics interfaces theme of the seeder Research Center so I suppose the main challenge that we're working on is to take the tools and techniques that we've got in in big data analytics and make those available to as many people as possible and we're trying to do that through the development of I suppose interesting interfaces and interesting applications that take pretty sophisticated and pretty interesting techniques and put those in the hands of I suppose ordinary business users and who don't have a massive amount of analytics expertise I suppose that that's particularly feasible at the moment because the technology is really starting to mature in the range of industries and applications has been used in is really starting to grow the big thing that we get that's great is we get data so the big challenge that we have as academics trying to do this kind of research is getting access to real-world large data sets that represent all the messiness and all the complications that goes on when you try and use analytics analytics techniques kind of in the wild and what the companies are bringing to us is that I suppose what the companies are doing that's great is giving us access to that real data as the second thing that's brilliance is that the companies are coming to us with interesting problems to solve and those problems tend to be just maybe a little bit different than the perspectives that we'd have on them from an academic background the thing that we offer in the thing that we can do is start to look at those questions that are just out beyond what the companies can look at themselves so those I suppose reach those questions that are maybe just this side of the cutting edge and so technologies and research that's been a little bit proven but isn't ready for application just yet and isn't on that the core roadmaps that companies have we're I suppose we have the time the capacity to look at those questions figure out how those kind of techniques and solutions could be best used by companies who are working analytics and then I still share that knowledge with companies so that they can roll that into their their product roadmaps you

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