Decoding Big Data: Mengubah Data Menjadi Keunggulan Kompetitif dalam Pengambilan Keputusan Bisnis
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Penelitian ini mengkaji peran Big Data dalam menciptakan keunggulan kompetitif bagi perusahaan melalui pendekatan analitik yang mencakup metode deskriptif, prediktif, dan preskriptif. Dengan menggunakan studi kasus empiris di berbagai sektor industri seperti ritel, keuangan, dan kesehatan, penelitian ini menunjukkan bahwa pemanfaatan Big Data memungkinkan organisasi untuk mengidentifikasi peluang pasar, memitigasi risiko, dan meningkatkan efisiensi operasional. Pendekatan bibliometrik yang diterapkan membantu dalam memetakan tren penelitian terkait Big Data, termasuk identifikasi kolaborasi antar peneliti dan kluster riset dominan. Hasil studi menunjukkan bahwa perusahaan yang secara optimal mengintegrasikan Big Data ke dalam proses pengambilan keputusan mampu merespons dinamika pasar dengan lebih cepat, mengurangi biaya operasional, dan memperkuat loyalitas pelanggan. Selain itu, analitik Big Data memungkinkan prediksi yang lebih akurat terhadap tren pasar dan perilaku konsumen, yang berujung pada inovasi produk dan layanan yang lebih relevan. Penelitian ini juga menyoroti pentingnya kepemimpinan transformasional dalam memfasilitasi implementasi Big Data, serta tantangan yang dihadapi organisasi terkait privasi dan keamanan data. Dengan demikian, penelitian ini memberikan kontribusi signifikan bagi pemahaman tentang pentingnya Big Data dalam pengembangan strategi bisnis yang berbasis data di era digital.
Author Biographies
Program Studi Kewirausahaan, Institut Teknologi dan Bisnis Muhammadiyah Bali, Kabupaten Jembrana, Provinsi Bali, Indonesia.
Program Studi Bisnis Digital, Institut Teknologi dan Bisnis Muhammadiyah Bali, Kabupaten Jembrana, Provinsi Bali, Indonesia.
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References
Cheng, O. and Lau, R. (2015). Big data stream analytics for near real-time sentiment analysis. Journal of Computer and Communications, 03(05), 189-195. https://doi.org/10.4236/jcc.2015.35024
Devie, D., Wendrata, I., & Hartono, C. (2018). The impacts of transformational leadership on competitive advantage of local accounting firms. Journal of Economics and Business, 1(4). https://doi.org/10.31014/aior.1992.01.04.47
Muniswamaiah, M., Agerwala, T., & Tappert, C. (2019). Data virtualization for decision making in big data. International Journal of Software Engineering & Applications, 10(5), 45-53. https://doi.org/10.5121/ijsea.2019.10503
Ochuba, N. (2024). Strategies for leveraging big data and analytics for business development: a comprehensive review across sectors. Computer Science & It Research Journal, 5(3), 562-575. https://doi.org/10.51594/csitrj.v5i3.861
Olszak, C. and Zurada, J. (2019). Big data-driven value creation for organizations.. https://doi.org/10.24251/hicss.2019.021
Otchere, S., Tian, H., Coffie, C., & Hammond, F. (2021). Heterogeneous analysis of the nexus between big data analytics and value co-creation: insight from selected service businesses in ghana. Technium Social Sciences Journal, 25, 533-543. https://doi.org/10.47577/tssj.v25i1.4869
Provost, F. and Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big Data, 1(1), 51-59. https://doi.org/10.1089/big.2013.1508
Sayed, R. (2023). Ethical considerations in the use of big data for business analytics: а cross-industry perspective. Journal of Innovations and Sustainability, 7(4), 08. https://doi.org/10.51599/is.2023.07.04.08
Sazu, M. and Jahan, S. (2022). Can big data analytics improve the quality of decision-making in businesses?. Iberoamerican Business Journal, 6(1), 04-27. https://doi.org/10.22451/5817.ibj2022.vol6.1.11063
Tan, K. and Zhan, Y. (2016). Improving new product development using big data: a case study of an electronics company. R and D Management, 47(4), 570-582. https://doi.org/10.1111/radm.12242
Wamba, S. (2017). Big data analytics and business process innovation. Business Process Management Journal, 23(3), 470-476. https://doi.org/10.1108/bpmj-02-2017-0046
Watson, H. (2014). Tutorial: big data analytics: concepts, technologies, and applications. Communications of the Association for Information Systems, 34. https://doi.org/10.17705/1cais.03465
William, H. (2023). Harnessing data virtualization for informed decision making in big data.. https://doi.org/10.31219/osf.io/g9mx3
Yangailo, T. (2023). Assessing the influence of transformational leadership on competitive advantage through important innovations and quality results: case of railway industry. Management Science Letters, 13(1), 41-50. https://doi.org/10.5267/j.msl.2022.9.003
(2016). Scalable and flexible big data analytic framework (sfbaf) for big data processing and knowledge extraction.. https://doi.org/10.15242/iie.e0116024
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