Document Type

Article

Original Publication Date

2016

Journal/Book/Conference Title

Decision Support Systems

Volume

91

First Page

1

Last Page

12

DOI of Original Publication

10.1016/j.dss.2016.07.003

Comments

Originally published at http://doi.org/10.1016/j.dss.2016.07.003.

Date of Submission

January 2017

Abstract

The rapid growth of big data environment imposes new challenges that traditional knowledge discovery and data mining process (KDDM) models are not adequately suited to address. We propose a snail shell process model for knowledge discovery via data analytics (KDDA) to addrets these challenges. We evaluate the utility of the KDDA process model using real-world analytic case studies at a global multi-media company. By comparing against traditional KDDM models, we demonstrate the need and relevance of the snail shell model, particularly in addressing faster turnaround and frequent model updates that characterize knowledge discovery in the big data environment.

Rights

© 2016 Elsevier B.V. All rights reserved.

Is Part Of

VCU Dept. of Management Publications

Included in

Business Commons

Share

COinS