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Big Data Visualization Tool: a Best-Practice Selection Model
German University in Cairo.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-4250-4752
Number of Authors: 2
2017 (English)In: IADIS Information Systems Conference (IS 2017) / [ed] Powell P.,Rodrigues L.,Nunes M.B.,Isaias P., Institute of Electrical and Electronics Engineers (IEEE), 2017, 59-68 p.Conference paper, Published paper (Refereed)
Abstract [en]

Big data visualization tools are analytical tools used by organizations for the purpose of discovering knowledge. With the support of interactive visual interfaces, methods and techniques for analyzing big data are applied to facilitate the knowledge discovery process and provide domain relevant insights. Many studies, both academic and industrial, have been conducted in order to investigate visualization tools. However, little research has been conducted in order to study how big data visualization tools could be selected. Consequently, this research is setout to fill-in this gap. Accordingly, a three phases (literature review, Delphi method, and exploratory case study) research process is conducted to propose a big data visualization tool best-practice selection model. The use of this model would help organizations in selecting and obtaining the appropriate visualization tool. The results of this research revealed a number of criteria elements, which formulate the best-practice model for big data visualization tool selection. A total number of 36 criteria have been agreed upon by a number of 14 big data experts. Such criteria belong to six main types: technical, visualization, collaboration & mobility, operational, data governance and managerial requirements. An exploratory case study was conducted on a multi-national telecommunication company in order to test the usability of the model, which attained positive feedback results.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. 59-68 p.
Keyword [en]
Big data analytics, big data visualization tools, selection procedure, Delphi method
National Category
Information Systems, Social aspects
Research subject
Information systems
Identifiers
URN: urn:nbn:se:ltu:diva-61861Scopus ID: 2-s2.0-85032360067OAI: oai:DiVA.org:ltu-61861DiVA: diva2:1072292
Conference
10th IADIS International Conference on Information Systems 2017, Budapest, 10-12 April 2017
Available from: 2017-02-07 Created: 2017-02-07 Last updated: 2017-11-24Bibliographically approved

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Elragal, Ahmed

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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Output format
  • html
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  • asciidoc
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