ICEIS 2004 Proceedings of the Sixth International Conference on Enterprise Information Systems

Data warehouse related technologies, allows to extract, group and analyze historical data in order to identify information valuable to decision making processes. In this paper the implementation of a weather data warehouse (WDW) to store Mexico’s weather variables is presented. The weather variables data were provided by the Mexican Institute for Water Technologies (IMTA), the IMTA does research, development, adaptation, human resource formation and technology transfer to improve the Mexico’s water management, and in this way contribute to the sustainable development of Mexico. The implemented WDW contains two dimension tables (one time dimension table and, one geographical dimension table) and one fact table (that stores the data values for weather variables). The time dimension table spans over ten years from 1980 to 1990. The geographical dimension table involves many Mexico’s hydrological zones and comes from 5551 measuring stations. The WDW enables (through the dimensions navigation) the identification of weather patterns that would be useful for: a) agriculture politics definition; b) climatic change research; and c) contingency plans over weather extreme conditions. Even it is well known, but it is important to mention, that the data warehouse paradigm (in many cases) is better to derivate knowledge from the data in comparison to the database paradigm, a fact that was confirmed through the WDW exploitation.