UPM Institutional Repository

Big data analytics implementation for value discovery: a systematic literature review


Citation

Adrian, Cecilia and Sidi, Fatimah and Abdullah, Rusli and Ishak, Iskandar and Affendey, Lilly Suriani and A. Jabar, Marzanah (2016) Big data analytics implementation for value discovery: a systematic literature review. Journal of Theoretical and Applied Information Technology, 93 (2). pp. 385-393. ISSN 1992-8645; ESSN: 1817-3195

Abstract

The growing number of big data technologies and analytic solutions has been developed to support the requirement of big data implementation. The capability of analyzing big data becomes critical issues in the big data implementation because the traditional analytics tools are no longer suitable to process and analyze the massive amount and different types of data. In the recent years, technological issues and challenges on big data adoptions have been actively conducted globally. However, there are still lacking of studies on how big data implementation can derive and discover values for better decision making. The intent of this review is to investigate the capability components for Big Data Analytics (BDA) implementation towards value discovery. Based on this investigation, it was found that the capability components that may impact value discovery is formulating big data framework that includes the enabler technology and processing and using sufficient analytic techniques for analysing big data.


Download File

[img]
Preview
PDF (Abstract)
Big data analytics implementation for value discovery a systematic literature review.pdf

Download (5kB) | Preview
Official URL or Download Paper: http://www.jatit.org

Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
Publisher: Little Lion Scientific R&D
Keywords: Big data analytics implementation; Capability Components; Processing, Analytics techniques; Value discovery
Depositing User: Ms. Nida Hidayati Ghazali
Date Deposited: 08 Dec 2017 08:43
Last Modified: 08 Dec 2017 08:43
URI: http://psasir.upm.edu.my/id/eprint/55196
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item