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Application Scenarios and Practice of Data Science in the Context of Big Data

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DOI: 10.23977/jeis.2023.080304 | Downloads: 6 | Views: 420


Jianwei Ren 1


1 University of Wisconsin-Madison, Seattle, 53711, USA

Corresponding Author

Jianwei Ren


With the development of the Internet, the era of BD (Big Data) is getting closer and closer. A country with mature BD has a future, and many enterprises cannot compete without BD. For example, BD can accurately position people's hobbies, the sales industry or service industry can use BD for precision marketing, and the development trend of BD includes data resource, data science, and the establishment of data alliances. Data science is a specialized discipline, a discipline born in the era of BD. It is at the intersection of statistics, machine learning and domain knowledge, and is an obvious interdisciplinary discipline. With the development of BD, data science must also develop with it. How data science develops and in which scenarios it can be applied remains to be studied. Through the research on BD and its development trend, and the theoretical research and analysis of data science, this paper aims to explore the specific application of data science, a new discipline, and practice it. Experiments have shown that applying data science to filtering spam and malware has a filtering rate of up to 95%. When applied to the sales industry, the predicted results are almost identical to the actual results. It has been confirmed that data science can collect, process, analyze data, and make predictive inferences. Data science can be applied to personalized content, navigation, and other scenarios that require prediction of results.


Big Data, Data Science, Practical Application, Interdisciplinary Disciplines


Jianwei Ren, Application Scenarios and Practice of Data Science in the Context of Big Data. Journal of Electronics and Information Science (2023) Vol. 8: 33-40. DOI:


[1] Yu Canqing, Li Liming. Data science in large cohort studies. Chinese journal of Epidemiology, 2019, 40(1):1-4. 
[2] Wang Kai, Zhang Shaojie, Ma Juan, et al. Study on spatial distribution and warning criteria of landslide macro displacement stage in big data environment. Advances in earth science, 2022, 37 (10): 1054-1065. The DOI: 10. 11867 / j. i SSN. 1001-8166. 2022. 042. 
[3] Huo Cunxiao, Hou Yu. Research on product design for the elderly in the era of Big Data. Packaging Engineering, 2019, 040(012):147-150. 
[4] Qiu Zixun, Zhou Yahong. Digital economy development and regional total factor productivity: Based on the analysis of national big data comprehensive pilot zone. Journal of Finance and Economics, 2021, 047(007):4-17. 
[5] Yao Na, Wang Xiao, Yang Chuanjiang, et al. Big data grid control equipment in the technical support system monitoring research. Journal of hydroelectric and water conservancy, 2022, 6 (7): 65-67. The DOI: 10. 12238 / HWR v6i7. 4509. 
[6] Qiu Huijun, Yuan Lianxiong, Huang Xuecun, et al. Study and analysis of symptom characteristics of Novel coronavirus pneumonia based on Internet big data. Chinese otolaryngology head and neck surg, 2020, 55 (6): 569-575. The DOI: 10. 3760 / cma. J. c. n115330-20200225-00128. 
[7] Jin Chensheng. Discussion on risks and preventive measures of small and micro enterprise credit business in commercial banks under the background of big data. Knowledge Economy, 2021, 590(023):11-12. 
[8] Xing Luyu, Hu Runhong, Tang Chensong. Computer Knowledge and Technology, 2021, 017(009):244-246. Python Big Data Mining Guest experience in Yixian County, Anhui Province. Computer Knowledge and Technology, 2021, 017(009):244-246. 
[9] Qu Jingquan. Challenges of macroeconomic analysis in the era of big data. Investment and Entrepreneurship, 2020, 031(017):26-28. 
[10] Yu Canqing, Li Liming. Data science in large cohort studies. Chinese journal of Epidemiology, 2019, 40(1):1-4. 
[11] Compiled by Zhang Juan. World Economic Forum released the report "Data Science in the new Economy". Research Information Technology and Application, 2019, 10(4):93-94. 
[12] Yang Yin, Huang Yunqing, Liu Shaoyue. Data in local colleges of science and technology of data professional personnel training mode research. Journal of education modernization, 2019, 6 (4): 23-25. DOI: CNKI: SUN: JYXD. 0. 2019-04-007. 
[13] Sun Jiling Li Xiaojing. Construction and innovation of Disability Statistics System on a new journey: Summary of the 6th Symposium on Disability Data Science and the Founding Conference of Disability Statistics Branch of China Statistical Society. Statistical Research, 2022, 39(2):158-160. 
[14] Cheng Shuo, Liu Guifeng, Liu Qiong. When Library and information science meets Data science: intersection and expansion. Library Forum, 2022, 42(11):94-100. 
[15] Singh A, Garg S, Kaur K,et al. Fuzzy-Folded Bloom Filter-as-a-Service for Big Data Storage in the Cloud. IEEE Transactions on Industrial Informatics, 2019, 15(4):2338-2348. DOI: 10. 1109/TII. 2018. 2850053. 
[16] Huang Y, Sheng K, Sun W. Influencing factors of manufacturing agglomeration in the Beijing-Tianjin-Hebei region based on enterprise big data. Acta Geographica Sinica, 2022, 32(10): 2105-2128. DOI: 10. 1007/ s11442-022-2039-9. 
[17] Diller G P, Baumgartner H. Impact of Adequate Provision of Care Models and Big Data Analysis for Adults with Congenital Heart Disease. Aktuelle Kardiologie, 2021, 10(05):403-407. DOI: 10. 1055/a-1556-0210. 
[18] Wang T, Zheng Z, Rehmani M H,et al. Privacy Preservation in Big Data from the Communication Perspective — A Survey. IEEE Communications Surveys & Tutorials, 2019, 21(1):753-778. DOI:10. 1109/COMST. 2018. 2865107. 
[19] Kulkarni A R, Kumar N, Rao K R. Efficacy of Bluetooth-Based Data Collection for Road Traffic Analysis and Visualization Using Big Data Analytics. Big Data Mining and Analytics, 2023, 6(2): 139-153. DOI: 10. 26599/ BDMA. 2022. 9020039. 
[20] Trenti T, Pecoraro V, Pirotti T,et al. IgM anti-SARS-CoV-2-specific determination: useful or confusing? Big Data analysis of a real-life scenario. Internal and emergency medicine, 2021, 16(8):2327-2330. DOI:10. 1002/jmv. 26830. 
[21] Hao L A, et al. Big data analysis of the internet of things in the digital twins of smart city based on deep learning. 2021, 128:167-177. 
[22] Lv Z, Lou R, Li J, et al. Big Data Analytics for 6G-Enabled Massive Internet of Things. IEEE Internet of Things Journal, 2021, PP (99):1-1.

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