Abstract
Big data is a challenging issue as its volume, shape, and size need to be modified in order to extract important information for a specific purpose. The amount of data is rising with the passage of time. This increase in volume can be a challenging issue to analyze the data for smooth industry and the Internet of things. Several tools, techniques, and mechanisms are available to support the handling and management process of such data. Decision support systems can be one of the important techniques which can support big data in order to make decisions on time. The proposed study presents a decision support system to deal with big data and scientific programming for the Industrial Internet of Things. The study has used the tool of SuperDecisions to plot the hierarchy of situations of big data and scientific programming and to select the best alternative among the available.
Highlights
Big data is termed to be a hot area of research which needs to be shaped in order to derive and extract meaningful information for the specific purpose of research. e data exist in different forms including structured, unstructured, and semistructured
We devise a scientific classification by characterizing and classifying the literature based on essential factors. e case studies and frameworks of the different endeavours were presented that have profited by big data analytics (BDA) [20]
For the analysis and management of big data, there is a need of tools and techniques to properly analyze, organize, and extract meaningful information for a specific purpose
Summary
Big data is termed to be a hot area of research which needs to be shaped in order to derive and extract meaningful information for the specific purpose of research. e data exist in different forms including structured, unstructured, and semistructured. Researchers try to come with a solution to extract meaningful information from the data of Industrial Internet of ings (IIoTs) in an effective and efficient way. Decision-making based on multicriteria is one of the most efficient problems solving mean to select appropriate decision among the number of choices. E research finds novel means to make the decision support system for the problems of various application domains by using multiple criteria in integration with machine learning and artificial intelligence. Researchers try to use multicriteria-based decision support system to integrate the effectiveness of power of machine learning algorithms to provide an intelligent decisionmaking alternative [8,9,10].
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