Framework for contextual consulting practices in adherence for decentralized data-driven decision making

Abstract

With the rising adoption of technological advancement and industry-based automation standards, the area of consulting firms is gradually evolving to keep up this pace towards incorporating sophisticated analytical operation for facilitating value-added consulting services. Review of existing practices of consulting firm shows increasing adoption of analytical process which leads to complex form of operation towards knowledge discovery of consulting data. Hence, this manuscript introduces a framework of contextual consulting practices where the core idea is to incorporate a baseline structure of knowledge discovery associated with consulting data in adherence of industry 4.0 automation standards. The framework takes the input of streamed consulting diversified data governed by a template-based entry-points where the consulting data is subjected to series of transformation operation that not only preprocess the consulting data but also optimizes the data to enhance its data quality. The study model is implemented in MATLAB considering an extensive analytical framework towards data-driven decision making and decentralization to exhibit proposed model to offer better analytical performance in contrast to existing study models.