Title:	BIG DATA VISUALIZATION TOOL: A BEST-PRACTICE SELECTION MODEL
Author(s):	Ayaallah Marawan Hassan and Ahmed Elragal
ISBN:	978-989-8533-62-3
Editors:	Miguel Baptista Nunes, Pedro Isaías and Philip Powell
Year:	2017
Edition:	Single
Keywords:	Big Data Analytics, Big Data Visualization Tools, Selection Procedure, Delphi Method
Type:	Full Paper
First Page:	59
Last Page:	68
Language:	English
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Full Contents:	click to dowload
Paper Abstract:	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.
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