부산대학교 도서관

Data analytics is providing benefits in different areas by generating value for organisations. The analysis of meteorological data is an area in which descriptive and predictive analytics can deliver high value to understand climate events better and use the information for different purposes like disaster prevention, climate change management, climate events prediction, increasing efficiency in economic sectors like fishing and agroindustry, and so on. This paper reports on the design, implementation and validation of the information supply chain (ISC) allowing data analytics for the network of weather stations Niño 5. The proposed ISC includes the data sources definition, the identification of the information recipients, the data acquisition and preparation for data analytics, and the design and validation of dashboards for descriptive analytics. The proposal is implemented using Tableau Desktop, Tableau Prep Builder and Tableau Online (Tableau Cloud). The proposal validation is done with stakeholders based on the importance of the Network Niño 5 in the study of the El Nino-Southern Oscillation, which has a relevant social impact and affects several economic sectors in South America. The results are promising and define the path to enhancing data analytics processes based on the data collected by the Network Niño 5.