A Study on the Aspects of Quality of Big Data on Online Business and Recent Tools and Trends Towards Cleaning Dirty Data

Citation

Goh, Michael Kah Ong and Hossen, Md Ismail and Rahman, Md. Armanur and Hossen, Abid (2020) A Study on the Aspects of Quality of Big Data on Online Business and Recent Tools and Trends Towards Cleaning Dirty Data. In: 2020 11th IEEE Control and System Graduate Research Colloquium (ICSGRC), 8 Aug. 2020, Shah Alam, Malaysia.

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Abstract

The reliability, efficiency, and accuracy of e-business depend on the quality of data that is associated with a buyer, seller, brokers, e-business portals, admins, managers, decision-makers and so on. However, maintaining the quality of data in e-business is very challenging. It is because e-business data typically comes from different communication channels and sources. Integrating and managing the data quality of different sources is generally much troublesome than dealing with traditional business data. Even though there are several data cleaning methods and tools exist those methods and tools have some constraints. None of them directly working, particularly on e-business data that motivates to do research to highlight the aspects of big data quality related to e-business. Therefore, this research demonstrates the problems related to data quality related to online business, discusses the existing literature of data quality, the current tools and techniques that are being used for data quality and provides a research finding highlighting the weaknesses of current tools to address the problem of online business.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Machine learning
Subjects: Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 20 Oct 2021 02:48
Last Modified: 20 Oct 2021 02:48
URII: http://shdl.mmu.edu.my/id/eprint/8303

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