Low-latency big data visualisation - Nicholas Tan Jerome
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Piegāde 15-21 darba dienu laikā
30 dienu atgriešanas politika
Diese Arbeit hat sich zum Ziel gesetzt, Methoden aufzuzeigen, ¿Big-Datä-Archive zu organisieren und zentrale Elemente der enthaltenen Informationen zu visualisieren. Anhand von drei wissenschaftlichen Experimenten werde ichzwei ¿Big-Datä- Herausforderungen, Datenvolumen (Volume) und Heterogenität (Variety), untersuchen und eine Visualisierung im Browser präsentieren, die trotz reduzierter Datenrate die wese ... Pilns apraksts
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Aprašymas
Diese Arbeit hat sich zum Ziel gesetzt, Methoden aufzuzeigen, ¿Big-Datä-Archive zu organisieren und zentrale Elemente der enthaltenen Informationen zu visualisieren. Anhand von drei wissenschaftlichen Experimenten werde ichzwei ¿Big-Datä- Herausforderungen, Datenvolumen (Volume) und Heterogenität (Variety), untersuchen und eine Visualisierung im Browser präsentieren, die trotz reduzierter Datenrate die wesentliche Information in den Datensätzenenthält. The scope of this research focuses on managing Big Data and eventually visualising the core information of the data itself. Specifically, I study three large-scale experiments that feature two Big Data challenges: large data size (Volume) and heterogeneous data (Variety), and provide the final visualisation through the web browser in which the size of the input data has to be reduced while preserving the vital information.
Vairāk informācijas
| Autors | Nicholas Tan Jerome |
|---|---|
| Izdevējs | Karlsruher Institut für Technologie |
| Izlaides gads | 2019 |
| Vāka tips | Mīkstais vāks |
| EAN | 9783731509400 |