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Solving problems with visual analytics: the role of visualization and analytics in exploring big data

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2013

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Gesellschaft für Informatik e.V.

Zusammenfassung

Never before in history data is generated and collected at such high volumes as it is today. As the volumes of data available to business people, scientists, and the public increase, their effective use becomes more challenging. Keeping up to date with the flood of data, using standard tools for data analysis and exploration, is fraught with difficulty. Visual analytics seeks to provide people with better and more effective ways to understand and analyze large datasets, while also enabling them to act upon their findings immediately. Visual analytics integrates the analytic capabilities of the computer and the abilities of the human analyst, allowing novel discoveries and empowering individuals to take control of the analytical process. Visual analytics enables unexpected and hidden insights, which may lead to beneficial and profitable innovation. In the visual analysis process, it is not obvious what can be done by automated analysis and what should be done by interactive visual methods. In dealing with massive data, the use of automated methods is mandatory - and for some problems it may be sufficient to only use fully automated analysis methods, but there is also a wide range of problems where the use of interactive visual methods is necessary. The talk presents the challenges of visual analytics and exemplifies them with several application examples, illustrating the exiting potential of current visual analysis techniques but also their limitations.

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Keim, Daniel (2013): Solving problems with visual analytics: the role of visualization and analytics in exploring big data. Datenbanksysteme für Business, Technologie und Web (BTW) 2014. Bonn: Gesellschaft für Informatik e.V.. PISSN: 1617-5468. ISBN: 978-3-88579-608-4. pp. 17-18. Regular Research Papers. Magdeburg. 13.-15. März 2013

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