Multidimensional Data Model for Air Pollution Data Analysis

A large volume of data being gathered and stored in a file is a remarkable rate. The administration and handling of an enormous amount of data consume a lot of time and space. Therefore, the procedure to store, maintain, analyze with an easy and useful format is an essential task. We describe a multidimensional data model to store, group and analyze for decision making with meaningful information from historical and current data. In this paper STAR schema and SNOWFLAKE schema for the multidimensional data model is proposed for organizing the data obtained from Taiwan Air Quality Monitoring Network (TAQMN). In the data model, there is a fact table, three dimensional tables and other parameters such as Min, Max, Mean, StdDev, and coefficient variation are considered as computational measures. The measures are analyzed for an effective decision making or knowledge discovery.