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dc.contributor.authorShou, Sike-
dc.date.accessioned2023-07-24T11:54:15Z-
dc.date.available2023-07-24T11:54:15Z-
dc.date.issued2023-07-20-
dc.identifier.urihttp://hdl.handle.net/2451/69533-
dc.descriptionInitially, the study was expected to find real-world examples of how data analysts use ChatGPT in their work. But the use of ChatGPT is forbidden in many companies because of privacy issues and data security. The study then turned to finding applications of ChatGPT to improve data analysts' work without directly utilizing company data and to improve the teaching quality of the MASY program with ChatGPT.en
dc.description.abstractContribution: Initially, the study was expected to find real-world examples of how data analysts use ChatGPT in their work. But the use of ChatGPT is forbidden in many companies because of privacy issues and data security. The study then turned to finding applications of ChatGPT to improve data analysts' work without directly utilizing company data and to improve the teaching quality of the MASY program with ChatGPT. Background: The main purpose of the study is to find applications of ChatGPT to improve the productivity of data analysts and improve the teaching quality of the MASY program. ChatGPT has surprised the world with its ability to perform various tasks, including writing Python/SQL code and doing large-scale data analysis. Many people argue data analysts may be replaced by ChatGPT. The paper aims to find the true situation of how data analysts use and view this tool. In addition, find out how can they use it efficiently to increase their productivity. For the MASY program with many database and analytics courses, the study also aims to find ways to integrate ChatGPT in teaching. Research Question: How is ChatGPT used in data analysts’ work and what are their views on this tool? What are the daily responsibilities of data analysts and how can ChatGPT boost their productivity without data leakage? How can ChatGPT be integrated in the teaching of analytics courses in the MASY program? Methodology: Both quantitative and qualitative approaches were employed. Quantitative results were obtained from interviews with working data analysts. Qualitative data were obtained from the interviews, and from the research literature and practices on ChatGPT. Findings: ChatGPT can perform many tasks of a data analyst but companies are reluctant to use it for analysis purposes because of privacy issues and data security. In the future, it is possible that many companies will develop their own local large language models to utilize their full potential. In addition, ChatGPT can make the preparation of teaching materials easier for professors and the studying process more efficient for students.en
dc.publisherNYU SPS Applied Analytics Laboratoryen
dc.rightsThis consent is exclusively for the public distribution and preservation of my work. It does not grant permission for any commercial use or publication of the work. For such purposes, the interested party must contact the author directly to secure additional permissions.en
dc.titleImplementing Generative AI Tools in Analyticsen
dc.typeTechnical Reporten
Appears in Collections:Applied Analytics Lab Working Papers

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