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Big data analytic application framework for Malaysian palm oil industry


Ishak, Iskandar and Sidi, Fatimah and Affendey, Lilly Suriani and Ibrahim, Hamidah and Mamat, Ali and Kamarulzaman, Nitty Hirawaty and Muharam, Farrah Melissa (2014) Big data analytic application framework for Malaysian palm oil industry. In: Malaysian National Conference of Databases 2014 (MaNCoD 2014), 17 Sept. 2014, Universiti Putra Malaysia, Serdang, Selangor. (pp. 1-6).


Big Data is a practice of collecting and processing large amount of data and always associated with analyzing these data. It also involves new approaches that are different than conventional information technology. Companies and business organizations uses this approach to gain new insights, assisting decision makings and business optimizations. Industry such as palm oil industries that consist of multiple activities along its upstream and downstream activities needs to employ Big Data approaches to ensure its sustainability in the world's edible oil market. Data from upstream activities such as planting, nursery and irrigation and downstream activities such as milling and refining are important to be collected and analyzed in order to gain new insights and to predict events such as market trend, supply and demand. In this paper we present our proposed Big Data Analytic Application Framework for Malaysian Palm Oil Industry. This framework is to provide palm oil industry players in Malaysia a platform to collect, process, analyze and provide analysis and business insights to help decision making by users involved in the palm oil industry.

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Official URL or Download Paper: http://mancod2014.blogspot.my/p/proceedings.html

Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Agriculture
Faculty of Computer Science and Information Technology
Keywords: Big data; Palm oil; Sentiment analysis; Data analytic; Database
Depositing User: Nursyafinaz Mohd Noh
Date Deposited: 20 Aug 2015 00:40
Last Modified: 29 Jul 2016 08:03
URI: http://psasir.upm.edu.my/id/eprint/39920
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