OLAP MULTIDIMENSIONAL MODEL FOR POLLUTANT EMISSIONS IN INDUSTRIAL INSTALLATIONS

Abstract

OLAP (On-Line Analytical Processing) performs multidimensional analysis of business data and provides the capability for complex calculations, trend analysis, and sophisticated data modeling. It became the fundamental foundation for Intelligent Solutions including Business Performance Management, Planning, Budgeting, Forecasting, Financial Reporting, Analysis, Simulation Models, Knowledge Discovery, and Data Warehouse Reporting. OLAP enables end-users to perform ad-hoc analysis of data in multiple dimensions, thereby providing the insight and understanding they need for better decision making. For achieving the main objective of the three years research PN2 Project “Sustainable Management System of Resources Used for Monitoring and Evaluating the Environmental Risks in Order to Prevent the Negative Effects and to Manage Crises Situations - MEMDUR”, code D11-037/18.09.2007, webpage: http://memdur.ssai.valahia.ro), in the second phase of the research, an analysis of the existing risk management systems was fulfilled and a solution based on the OLAP systems was proposed with the view of its implementation. The OLAP system designing was made based on the solution offered by Microsoft and it proposes a multidimensional model for data organizing which allows the analysis of data through various visualizations of multidimensional cubes. The multitude of possible views over the data collection together with the choosing of the convenient measures can be taken into account for the risk calculus when is needed to offer a real image on the air pollution rate as a result of different pollutants resulted from the industrial processes (Rădulescu 2005). Looking forward, a SOLAP (Spatial On-Line Analytical Processing) instrument will integrate the advantages offered by the Geographic Information System (GIS) with the OLAP applications ones. The classical data warehouse architecture (structured on three levels: data level, OLAP server level and client level) can be extended to a SOLAP model where spatial data (with related attributes), measures and hierarchies have to be added. At the OLAP server level, the metadata warehouse integrates concepts like the relational model, the multidimensional model and GIS concepts. (Rivest et all. 2003)