Challenges and Issues in Unstructured Big Data: A Systematic Literature Review

Nur Syafiqah, Mohd Nafis and Suryanti, Awang (2018) Challenges and Issues in Unstructured Big Data: A Systematic Literature Review. Advanced Science Letters, 24 (10). pp. 7716-7722. ISSN 1936-6612. (Published)

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In past years, data mining had been a standard approach to extract hidden knowledge or pattern known as Knowledge Discovery in Database (KDD). However, KDD approach is unable to handle a terabytes or petabytes of ’Big Data’. The presence of Big Data term arises due to the growth of data volume, velocity, variety, veracity, and value. The objectives of this study are to explore the various data types available in Big Data and current challenges in Big Data. A systematic literature review is conducted to fulfill the research objectives. Several research questions arise in this study for example what type of data available in Big Data as well as what are the major challenges and issues emerged from previous studies. The outcomes of this review identified three data types in Big Data which are unstructured, semi-structured and structured data. Besides, there are also three greatest challenges in Big Data which are data, processing and management challenge. The result also reveals that process challenge is the most critical challenge in Big Data. This extensive systematic literature review can contribute knowledge to the Big Data area as well as for future research.

Item Type: Article
Additional Information: JCR® Category: Multidisciplinary Sciences. Quartile: Q2
Uncontrolled Keywords: Data Mining; Big data; Unstructured Data; Structured Data; Computational Intelligence
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 27 Nov 2018 00:51
Last Modified: 27 Nov 2018 00:51
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