Big data platforms: in the lens of selection and evaluation approach

ABSTRACT

The manifestation of big data has brought about firms’ intense desires for analytical value creation besides crucial challenges to handle data processing. Unlocking the potentials of big data analytics depends on devising and setting up platforms through the big data value chain. Achieving these appropriate platforms is indispensable and necessitates a selection and evaluation method. To that end, in this research, a new fuzzy superiority and inferiority ranking approach for selecting and evaluating big data platforms has been investigated; and introduced. In the proposed approach, both functional and non-functional criteria for the big data platform were gathered and customized. For demonstrating the applicability of the method, a numerical example provided; and the suggested approach was used in a company case that had been encountered with this platform acquisition problem. Simplifying assessment and selection of the big data platform, and feasible procedure are the main values of the offered approach. The proposed approach is beneficial for buyer firms, vendors and industries of big data, considering more accurate evaluations and making better acquisition decisions.

KEYWORDS:

• Big data
• big data platforms
• evaluation
• fuzzy superiority and inferiority ranking (FSIR)

Disclosure statement

No potential conflict of interest was reported by the authors.