The MeetUp which followed the Big Data Europe plenary meeting with all project partners started with a welcome from Martin Kaltenböck (SWC), organiser of the event.
Next, Sören Auer (Fraunhofer IAIS, BDE Project Lead, Slideshare), presented the BDE project to the audience of 53 people. He explained that the ambition of the project was to facilitate the positive uses of big data, in the different areas presented and liaise with researchers, industry and other users of societal challenges. Auer informed that the “v”s of “volume” and “velocity” were broadly covered in the different societal challenges, but that “variety” needed more support. He explained the vision of enrich Big Data Technologies with a dedicated Semantic Layer for more precise analytics and data handling.
He mentioned that 40-50 percent of household electrical devices could be made more efficient thanks to predictions of peaks in wind and sunshine during the coming hours, as people may then wait to turn on the washing machine for instance until they can use mostly renewable energy to power it. This could be turned into a smartphone application to help people to have a smarter demand for energy.
He explained that BDE will developing pilots and new tools that can be used to import data through the platform and convert them and so on. For instance, in the social sciences, the project aims to use open budget data from the pan-European data portal, with information from a number of different cities and integrate them. He also informed that 125 interviews has been carried out in all the societal challenges and that project partners will continue to go back to the communities to ask for their input over the duration of the project.
Then, Mario Meir-Huber (Big Data Lead CEE, Teradata, Vienna – Austria) presented big data management models (e.g. RACE). He mentioned the notion of a “data lake” where customers put data in a specific place but then do not know how to analyse them, which means that they become useless. In a traditional data warehousing model, data is released over two years, however, with big data, you want to have results straight away. You want to see what is going in two months time. What has also changed is that some projects do not give the results you were expecting. Data quality not in place and cannot fulfill business requirements. He informed that RACE analyses 50 big data projects which are in hectare bytes, which means that getting data ready takes some time. The issue is that customers would like to have results in a few months’ time, which makes it a challenging process. To begin with, you have to develop first insights and then see if the business in question are getting what they expect and later finalise these insights and evaluate the topics. He mentioned a collaboration exercise together with the University of applied sciences in Salzburg and the Institute of Science and Technology in Vienna on smart meters.
The last speaker, Zoltan C Toth (Senior Big Data Engineer RapidMiner Inc., Budapest – Hungary, Slides on Prezi) presented a selection of big data projects in Budapest, where big data is picking up. He mentioned that Spark was the “new big data king”. Teaching at Central European University, a private university in Budapest, Toth explained that academia was not attractive in Hungary, so people tend to work for private companies instead. His examples included Morgan Stanley, T-mobile and telenor.