
Data Analysis Transformation: Analysis of the Impact of ChatGPT on Various Industry Application
- 1 Business School, University of Sydney, Sydney, Australia
* Author to whom correspondence should be addressed.
Abstract
This research investigates Chat Generative Pre-Trained Transformer (ChatGPT)'s potential to significantly transform data analysis across various industries. As an advanced artificial intelligence language model, ChatGPT offers innovative solutions for automating and refining data analysis processes. Its applications are extensive, encompassing fields such as education, commerce, healthcare, and the military. The study provides a thorough assessment of ChatGPT's capabilities, highlighting its strengths in generating actionable insights and enhancing decision-making efficiency. Additionally, it evaluates the obstacles and constraints linked to artificial intelligence, encompassing apprehensions regarding data privacy, security, biases, and the precision of outcomes. By conducting detailed analyses of practical implementations and comparing them with previous research, this study emphasizes the considerable impact of ChatGPT while also underscoring the need for cautious and responsible use. The findings indicate that while ChatGPT holds significant promise for transforming data analytics, additional research and development are essential to enhance its performance and address potential risks. The study calls for ongoing investigation to address these challenges and maximize the benefits of ChatGPT in the evolving landscape of data analysis.
Keywords
ChatGPT, Data Analytics, Artificial Intelligence
[1]. Biswas, S.S. (2023) Potential use of chat gpt in global warming. Annals of biomedical engineering, 51(6), 1126-1127.
[2]. Waghmare, C. (2023) Introduction to ChatGPT. Unleashing The Power of ChatGPT: A Real World Business Applications. Berkeley, CA: Apress, 1-26.
[3]. Lo, C.K. (2023) What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), 410.
[4]. George, A.S., George, A.S.H. (2023) A review of ChatGPT AI's impact on several business sectors. Partners universal international innovation journal, 1(1), 9-23.
[5]. Ellis, A.R., Slade, E. (2023) A new era of learning: considerations for ChatGPT as a tool to enhance statistics and data science education. Journal of Statistics and Data Science Education, 31(2), 128-133.
[6]. Dibble, M. (2023) Schools ban ChatGPT amid fears of artificial intelligence-assisted cheating. VOA News.
[7]. Schmidt, L., Olorisade, B.K., McGuinness, L.A., et al. (2020) Data extraction methods for systematic review (semi) automation: A living review protocol. F1000Research, 9.
[8]. Mann, B., Ryder, N., Subbiah, M., et al. (2020) Language models are few-shot learners. arXiv preprint:2005.14165, 1.
[9]. Ouyang, L., Wu, J., Jiang, X., et al. (2022) Training language models to follow instructions with human feedback. Advances in neural information processing systems, 35, 27730-27744.
[10]. Achiam, J., Adler, S., Agarwal, S., et al. (2023) Gpt-4 technical report. arXiv preprint:2303.08774.
[11]. Tlili, A., Shehata, B., Adarkwah, M.A., et al. (2023) What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart learning environments, 10(1), 15.
[12]. Xu, Y., Shieh, C.H., van, Esch, P., et al. (2020) AI customer service: Task complexity, problem-solving ability, and usage intention. Australasian marketing journal, 28(4), 189-199.
[13]. Wang, W., Liu, H., Lin, W., et al. (2020) Investigation on works and military applications of artificial intelligence. IEEE Access, 8, 131614-131625.
Cite this article
Wang,L. (2024). Data Analysis Transformation: Analysis of the Impact of ChatGPT on Various Industry Application. Advances in Economics, Management and Political Sciences,135,116-122.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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