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Auflistung nach Schlagwort "data analysis"

1 - 6 von 6
  • Zeitschriftenartikel
    Assoziationsregeln – Analyse eines Data Mining Verfahrens
    (Informatik-Spektrum: Vol. 19, No. 5, 1996) Bollinger, Toni
  • Konferenzbeitrag
    DeLorean: A Storage Layer to Analyze Physical Data at Scale
    (Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Kußmann, Michael; Berens, Maximilian; Eitschberger, Ulrich; Kilic, Ayse; Lindemann, Thomas; Meier, Frank; Niet, Ramon; Schellenberg, Margarete; Stevens, Holger; Wishahi, Julian; Spaan, Bernhard; Teubner, Jens
    Modern research in high energy physics depends on the ability to analyse massive volumes of data in short time. In this article, we report on DeLorean, which is a new system architecture for high-volume data processing in the domain of particle physics. DeLorean combines the simplicity and performance of relational database technology with the massive scalability of modern cloud execution platforms (Apache Drill for that matter). Experiments show a four-fold performance improvement over state-of-the-art solutions.
  • Konferenzbeitrag
    The Evolving Landscape of UX Research in Industry: How AI is Transforming Manual Practices
    (Mensch und Computer 2024 - Usability Professionals, 2024) Li, Zhenni; Wang, Yu-Ling; Zhang, Bo; Klein, Andreas
    Artificial intelligence (AI) significantly impacts research techniques, strategic decision-making, and result quality control. This study explores how current AI tools reshape user experience research (UXR), their limitations, and future concerns. Insights from interviews with UX researchers and a focus group with UX consultants in China reveal AI’s effectiveness in supporting repetitive tasks, automating workflows, and showing impressive contextual synthesis abilities. However, human judgment remains crucial, and satisfaction with AI is moderate due to data security, regulatory challenges, and the complexity of new tools. The experts emphasized balanced AI integration, ensuring it complements human efforts without replacing human expertise. Strategic implementation and continuous evolution are key to maximizing AI’s potential. Experts suggested that future research should focus on developing AI tools tailored to specific needs, fostering innovation and motivation.
  • Zeitschriftenartikel
    eXtensible Business Reporting Language (XBRL)
    (Wirtschaftsinformatik: Vol. 44, No. 5, 2002) Nutz, Andreas; Strauß, Markus
    The eXtensible Business Reporting Language, or XBRL, is a royalty-free language based on XML that provides for a standardization of method and content in the exchange of business information. XBRL aims to reduce inefficiencies in data exchange and analysis, coupled with an improved comparability of information.The first taxonomies based on XBRL have: •identified opportunities for significant improvement in the efficiency of data exchange and automated analysis.•shown that comparisons between and the compatibility of information within business reports have not improved due to XBRL.
  • Textdokument
    MAGPIE: A Scalable Data Storage System for Efficient High Volume Data Queries
    (BTW 2019, 2019) Lindemann, Thomas; Brinkmann, Patrick; Dalbah, Fadi; Hakert, Christian; Honysz, Philipp-Jan; Matuszczyk, Daniel; Müller, Nikolas; Schmulbach, Alexander; Todorinski, Stefan Petyov; Tüselmann, Oliver; Wonsak, Shimon; Teubner, Jens
    Modern challenges in huge sized data storage and querying require new approaches in the field of data storage systems. With MAGPIE, we are introducing a hardware-software-co-design, which is efficient in querying data by distributed storage with storage-near pre-processing and designed to be scalable up to large dimensions.
  • Konferenzbeitrag
    Statistical Analysis of Eye Movement Data for Beginners
    (Proceedings of Mensch und Computer 2024, 2024) Grabinger, Lisa; Mottok, Jürgen Horst
    Data processing and (statistical) data analysis are important tasks in empirical research. However, they present a particular hurdle for beginners. For one, they require knowledge of statistical methods, their prerequisites, or use cases; For another, one needs either programming skills or some software system to carry out the analyses efficiently. Empirical eye tracking research poses a further hurdle; Data from an eye tracker is processed more elaborately and usually merged with data from other sources (e.g., questionnaires). In this article, we take a closer look at the possibilities that prospective eye tracking researchers have on their way from data collection to publication-ready analysis. We show that there is currently no software system that allows valid statistical analyses of eye tracking data to be performed without prior knowledge – which means that prospective eye tracking researchers need to learn or be taught the basics before performing actual analyses. As a solution, we present a novel tool: eyenalyzer. It guides through the analysis process – even without prior knowledge and therefore suitable for beginners. In the article, after highlighting the need for the tool, we discuss its development, give a glimpse at the user interface, and point out contribution and future work.