Actionable Knowledge As A Service (AKAAS): Leveraging big data analytics in cloud computing environments

Abstract

Knowledge-as-a service is an emerging research trend that constitutes a promising path for organizations aiming to achieve better customer support and decision-making across a wide range of content providers. However, only few studies have explored how traditional knowledge management processes and practices are challenged and evolve in relation to social and technological transformation stemming from the new age of cloud-computing environments. This research paper attempts to answer this gap by introducing a new framework for the management of knowledge in the cloud. The objective of this study is twofold. First, it aims to develop a knowledge-based decision framework using recent knowledge-as-as-service paradigms for creating, retrieving and reusing technical knowledge in cloud environments. Second, and in relation to this view, the current state of data analysis (business intelligence, big data analytics) is assessed in light of cloud computing environments and the simultaneous emergence of new knowledge management paradigms. An overview of cloud computing challenges is given as well as a representation of supporting knowledge management processes, followed by the description of related applications of the AKAAS (Actionable Knowledge As A Service) operating framework. The first part of the research develops upon literature on Knowledge Management Systems (KMS) frameworks. The second part of this study examines and assesses the nature of data and analytics required to provide on-demand delivery of knowledge in the cloud. Finally, the third part of the paper explores practical applications of the framework to guide the development of knowledge management processes and practices towards internal and external users adoption. We conclude by suggesting future research directions, including case studies examining differential knowledge cloud-based designs.