김성훈, 노명일, 김기수, 오민재, 구남국, "조선해양 산업용 PLM 데이터의 다차원화를 위한 ETL 프로세스 연구", 2017년도 한국CDE학회 동계학술발표회, 평창, pp. 26, 2017.02.08-10
| Abstract | Recently, the amount and the complexity of data have been increased due to the development of information and communication technology, and industry’s interest in big data technology is increasing day by day. Likewise, in the ship and offshore industry, interest in effective utilization of PLM data through big data technology is increasing because various and vast amounts of data are generated during the design, production, and operation processes and they are stored in the PLM (Product Lifecycle Management) database. In order to apply big data technology to PLM data, servers should be first constructed based on big data architecture and then, the PLM data should be stored in a format that is suitable for big data analysis on the servers. In this study, we construct servers with Hadoop, which is a representative big data technology, and use a ETL (Extraction, Transformation, Loading) tool to import PLM data from the existing PLM database into the servers. Then, we save the PLM data as a multidimensional form which is appropriate for big data analysis. |
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| Publication Date | 2017-02-08 |
김성훈, 노명일, 김기수, 오민재, 구남국, "조선해양 산업용 PLM 데이터의 다차원화를 위한 ETL 프로세스 연구", 2017년도 한국CDE학회 동계학술발표회, 평창, pp. 26, 2017.02.08-10