Predictive Analytics in Business Analytics: Decision Tree

Chee Sun Lee, Peck Yeng Sharon Cheang and Massoud Moslehpour ()
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Chee Sun Lee: School of Management, Universiti Sains Malaysia
Peck Yeng Sharon Cheang: School of Management, Universiti Sains Malaysia

Advances in Decision Sciences, 2022, vol. 26, issue 1, 1-30

Abstract: Business Analytics was defined as one of the most important aspects of combinations of skills, technologies and practices which scrutinize a corporation's data and performance to transpire data-driven decision-making analytics for a corporation's future direction and investment plans. In this paper, much of the focus will be given to predictive analytics, which is a branch of business analytics that scrutinize the application of input data, statistical combinations and intelligence machine learning statistics on predicting the plausibility of a particular event happening, forecast future trends or outcomes utilizing on-hand data with the final objective of improving the performance of the corporation. While it has been around for decades, predictive analytics has gained much attention in the late 20th century. This technique includes data mining and big data analytics. Last but not least, the decision tree methodology, a supervised simple classification tool for predictive analytics, is fully scrutinized below for applying predictive business analytics and decision tree in business applications.

Keywords: Business Analytics (BA); Predictive Analytics (PA); Machine Learning (ML); Decision Tree (DT) (search for similar items in EconPapers)
JEL-codes: D70 D79 D81 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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