Abstract—This article explores problem-driven computing and analytics. More specifically, it presents a disciplinary perspective on computing. It examines problem-driven computing and eSMACS computing. This research has three main contributions to the literature and the academia. The first contribution is that computing as a meta discipline consists of computing science, computing technology, computing engineering, computing system, computing intelligence, and computing management. The second contribution is problem-driven computing. The research demonstrates that a class of problems can be classified into four categories: descriptive problems, diagnostic problems, predictive problems, and prescriptive problems. Each of these problems drives a corresponding computing, that is, descriptive computing, diagnostic computing, predictive computing, and prescriptive computing. Descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics are examples of the mentioned four types of computing, correspondingly. The third contribution is that eSMACS computing as the digital computing and the example of problem-driven computing will play an important role in the digital age. The proposed approach in this research will facilitate the research and development of computing, big data analytics, intelligence, and data science.
Index Terms—Computing, intelligence, analytics, problem-driven computing, eSMACS computing, DDPP computing.
Zhaohao Sun is with Department of Business Studies, PNG University of Technology, Papua New Guinea (e-mail: zhaohao.sun@pnguot.ac.pg, zhaohaosun@gmail.com).
Cite: Zhaohao Sun, "Problem Driven Computing and Analytics," International Journal of Future Computer and Communication vol. 11, no. 3, pp. 52-60, 2022.
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