A Multi-criteria Group Decision Making Method for Selecting Big Data Visualization Tools

Abstract

Big data visualization tools are providing opportunities for businesses to strengthen decision making and achieve competitive advantages. Evaluating and selecting the most suitable big data visualization tool is however challenging. To effectively deal with this issue, this paper presents a multicriteria group decision making method for evaluating and selecting of big data visualization tools. Intuitionistic fuzzy numbers are used to tackle the subjectiveness and imprecision of the decision making process. The concept based on ideal solutions is applied for producing a relative closeness coefficient value for every big data visualization tool alternative across all evaluation criteria. A big data visualization tool selection problem is presented to demonstrate the applicability of the method.