Yi-Hsiung Lin*｜Center for Teaching and Learning, National Kaohsiung University, Kaohsiung, Taiwan｜rslin@nuk.edu.tw
Mi-Chia Ma｜Department of Statistics, Institute of Data Science, and Center for Innovative FinTech Business Models of National Cheng Kung University, Tainan, Taiwan｜mcma@ncku.edu.tw
Yu-Chi Li｜Center for Teaching and Learning, National Kaohsiung University, Kaohsiung, Taiwan｜jomireli@mail.cgust.edu.tw
*Corresponding author
▌Abstract
Web3 data analysis and data visualization are important topics in the field of data science. However, there is currently a lack of effective systematic methods for handling Web3 data analysis. Therefore, this study introduces an ELT (Extract, Transform, Load) process to explore methods for Web3 data analysis and the design of Web3 data visualization. It is implemented in two example projects: OpenSea secondary NFT market data and STEPN user data. The goal is to leverage modern and innovative internet technologies and data analysis systems to transform the findings from Web3 data analysis into actionable knowledge.
Keywords: data analysis, data visualization, Web3