Auflistung nach Schlagwort "data analysis"
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- ZeitschriftenartikelAssoziationsregeln – Analyse eines Data Mining Verfahrens(Informatik-Spektrum: Vol. 19, No. 5, 1996) Bollinger, Toni
- KonferenzbeitragDeLorean: 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, JensModern 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.
- ZeitschriftenartikeleXtensible Business Reporting Language (XBRL)(Wirtschaftsinformatik: Vol. 44, No. 5, 2002) Nutz, Andreas; Strauß, MarkusThe 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.
- TextdokumentMAGPIE: 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, JensModern 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.