ComEngApp : Computer Engineering and Applications Journal
Vol 6 No 2 (2017)

Creating a Business Value while Transforming Data Assets using Machine Learning

Ivana Dimitrovska (Faculty of Information and Communication Technology, FON University Skopje, Republic of Macedonia)
Toni Malinovski (Faculty of Information and Communication Technology, FON University Skopje, Republic of Macedonia)



Article Info

Publish Date
12 Jun 2017

Abstract

Machine learning enables computers to learn from large amounts of data without specific programming. Besides its commercial application, companies are starting to recognize machine learning importance and possibilities in order to transform their data assets into business value. This study explores integration of machine learning into business core processes, while enabling predictive analytics that can increase business values and provide competitive advantage. It proposes machine learning algorithm based on regression analysis for a business solution in large enterprise company in Macedonia, while predicting real-value outcome from a given array of business inputs. The results show that most of the machine learning predictive values for the desired process output deviated from 0 to 15% of actual employees' decision. Hence, it verifies the appropriateness of the chosen approach, with predictive accuracy that can be meaningful in practice. As a machine learning case study in business context, it contains valuable information that can help companies understand the significance of machine learning for enterprise computing. It also points out some potential pitfalls of machine learning misuse.

Copyrights © 2017






Journal Info

Abbrev

comengapp

Publisher

Subject

Computer Science & IT Engineering

Description

ComEngApp-Journal (Collaboration between University of Sriwijaya, Kirklareli University and IAES) is an international forum for scientists and engineers involved in all aspects of computer engineering and technology to publish high quality and refereed papers. This Journal is an open access journal ...