Communication and Knowledge – Big Data

Big data takes huge quantities of disparate data and puts it together for analysis. The information can come from all sorts of places: e-mails, online articles, comments on social networks such as Facebook, LinkedIn or Google+, videos, photos, audio files or even measurement values. But wherever the information has come from, the aim remains the same – to spot patterns. But since these data sets are so huge and unordered, you can’t expect to make sense of them with a traditional database or conventional analysis tools. Now new data mining tools and techniques are to make these mountains of data useful and manageable. The intention is to use the insights gained commercially.

The discussion about Big Data is about much more than the clever and profitable analysis of Internet data. In the age of the fourth Industrial Revolution and the emergence of cyber-physical systems and ultimately highly integrated Smart Ecosystems, the issue is to generate actually tangible added value for companies and individuals from the potential availability of a seemingly endless stream of data.

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Currently, the european energy markets are strongly affected by deregulation and the accelerated growth of centralized and decentralized fluctuating power supply. To cope with these challenges in the future, an economic, ecological, efficient and secure power supply through a holistic view of the involved processe s is required. EMS-PROPHET EDM features a powerful time series management, a comprehensive energy data management, with modules for power usage and accounting grid management, a scheduler for automation of energy business processes and an optimization and forecasting module for sustainable energy management.

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We make millions of financial transactions using our credit cards every day – and card fraud is on the rise. Researchers from Fraunhofer IAIS have joined forces with the company PAYMINT to develop the MINTify rule fraud identification system. This system reliably identifies attempted fraud even amid huge quantities of data. The latest data mining technologies lie at the heart of the system. »Our software analyzes data within a database to identify patterns and derive rules that can be carried over to fraud prevention systems,« explains Dr. Stefan Rüping from Fraunhofer IAIS. The technique involves systematically calculating all the possible statistical permutations of fraud patterns. This makes it possible to find new instances and patterns of misuse independently and to automatically translate this into transparent, readable rules.

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