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Beyond the Hype of Big Data Analytics Deployment: Conceptualization and Challenges Epistemology

Author

Listed:
  • Sharina Tajul Urus
  • Intan Waheedah Othman
  • Zarinah Abdul Rasit
  • Noraizah Abu Bakar
  • Sharifah Nazatul Faiza Syed Mustapha Nazri

Abstract

Businesses, government sectors, academia and society have been flooded with data which nowadays have become valuable economic assets. Data and Big Data Analytics (BDA) are vital for the succession of any organization. Big Data Analytics (BDA) delineates the approaches utilized to examine, process, analyze and expose hidden underlying patterns, interesting relations, and intelligence from huge datasets for different purposes. Despite the growth and widespread use of data analytics, the study on this research area is still at the nascent stage. The scenario is seen particularly for the developing countries like Malaysia. Previous literature has recognized data analytic development and its effect but has not yet provided a comprehensive review. This paper intends to conceptualize BDA manifestation, its application, and its challenges epistemology. This study employs a comprehensive review of past literature to serve the purpose. The findings of this paper will enhance the understanding of BDA conception epistemology (definition and application). This concept paper also intends to shed some light on BDA research areas by identifying the challenges surrounding BDA deployment. From the theoretical point of view, this paper contributes to providing BDA taxonomy based on the application in various industries. From the practical perspective, this paper contributes to BDA research field by identifying the obstacles that need to be managed by the BDA adopter for optimum utilization and decision making. From the government perspective, it contributes to Malaysian national agenda to becoming a leading regional BDA solution hub for all sectors and developed nation by the year 2025.

Suggested Citation

  • Sharina Tajul Urus & Intan Waheedah Othman & Zarinah Abdul Rasit & Noraizah Abu Bakar & Sharifah Nazatul Faiza Syed Mustapha Nazri, 2023. "Beyond the Hype of Big Data Analytics Deployment: Conceptualization and Challenges Epistemology," Business and Economic Research, Macrothink Institute, vol. 13(2), pages 74-111, December.
  • Handle: RePEc:mth:ber888:v:13:y:2023:i:2:p:74-111
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    References listed on IDEAS

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    1. Yaqoob, Ibrar & Hashem, Ibrahim Abaker Targio & Gani, Abdullah & Mokhtar, Salimah & Ahmed, Ejaz & Anuar, Nor Badrul & Vasilakos, Athanasios V., 2016. "Big data: From beginning to future," International Journal of Information Management, Elsevier, vol. 36(6), pages 1231-1247.
    2. Lars Hornuf & Milan F. Klus & Todor S. Lohwasser & Armin Schwienbacher, 2021. "How do banks interact with fintech startups?," Small Business Economics, Springer, vol. 57(3), pages 1505-1526, October.
    3. Yong-Hong Kuo & Andrew Kusiak, 2019. "From data to big data in production research: the past and future trends," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4828-4853, August.
    4. Canchu Lin & Anand S. Kunnathur & Long Li, 2020. "Conceptualizing big data practices," International Journal of Accounting & Information Management, Emerald Group Publishing Limited, vol. 28(2), pages 205-222, February.
    5. Faraway, Julian J. & Augustin, Nicole H., 2018. "When small data beats big data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 142-145.
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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