@inproceedings{Zhang2012-10Visua-22540,
  year={2012},
  doi={10.1109/VAST.2012.6400554},
  title={Visual Analytics for the Big Data Era - A Comparative Review of State-of-the-Art Commercial Systems},
  isbn={978-1-4673-4752-5},
  publisher={IEEE},
  booktitle={2012 IEEE Conference on Visual Analytics Science and Technology (VAST)},
  pages={173--182},
  author={Zhang, Leishi and Stoffel, Andreas and Behrisch, Michael and Mittelstädt, Sebastian and Schreck, Tobias and Pompl, René and Weber, Stefan Hagen and Last, Holger and Keim, Daniel A.}
}

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    <dcterms:bibliographicCitation>IEEE Conference on Visual Analytics Science &amp; Technology 2012 : Seattle, Washington, USA, 14 - 19 October 2012 ; Proceedings / Giuseppe Santucci and Matthew Ward (eds.). - Piscataway, NJ : IEEE, 2012, S. 173-182. - ISBN 978-1-4673-4753-2</dcterms:bibliographicCitation>
    <dc:creator>Weber, Stefan Hagen</dc:creator>
    <dc:contributor>Zhang, Leishi</dc:contributor>
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    <dc:rights>terms-of-use</dc:rights>
    <dc:creator>Mittelstädt, Sebastian</dc:creator>
    <dc:creator>Zhang, Leishi</dc:creator>
    <dc:language>eng</dc:language>
    <dc:contributor>Mittelstädt, Sebastian</dc:contributor>
    <dc:contributor>Last, Holger</dc:contributor>
    <dc:creator>Keim, Daniel A.</dc:creator>
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    <dc:contributor>Pompl, René</dc:contributor>
    <dcterms:abstract xml:lang="eng">Visual analytics (VA) system development started in academic research institutions where novel visualization techniques and open source toolkits were developed. Simultaneously, small software companies, sometimes spin-offs from academic research institutions, built solutions for specific application domains. In recent years we observed the following trend: some small VA companies grew exponentially; at the same time some big software vendors such as IBM and SAP started to acquire successful VA companies and integrated the acquired VA components into their existing frameworks. Generally the application domains of VA systems have broadened substantially. This phenomenon is driven by the generation of more and more data of high volume and complexity, which leads to an increasing demand for VA solutions from many application domains. In this paper we survey a selection of state-of-the-art commercial VA frameworks, complementary to an existing survey on open source VA tools. From the survey results we identify several improvement opportunities as future research directions.</dcterms:abstract>
    <dcterms:title>Visual Analytics for the Big Data Era - A Comparative Review of State-of-the-Art Commercial Systems</dcterms:title>
    <dc:contributor>Keim, Daniel A.</dc:contributor>
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    <dc:creator>Pompl, René</dc:creator>
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    <dc:creator>Last, Holger</dc:creator>
    <dc:creator>Stoffel, Andreas</dc:creator>
    <dc:contributor>Schreck, Tobias</dc:contributor>
    <dc:creator>Behrisch, Michael</dc:creator>
    <dc:contributor>Stoffel, Andreas</dc:contributor>
    <dcterms:issued>2012-10</dcterms:issued>
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    <dc:contributor>Behrisch, Michael</dc:contributor>
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