Building a Data Warehouse for National Social Security Fund of the Republic of Tunisia

The amounts of data available to decision makers are increasingly important, given the networkavailability, low cost storage and diversity of applications. To maximize the potential of these data withinthe National Social Security Fund (NSSF) in Tunisia, we have built a data warehouse as amultidimensional database, cleaned, homogenized, historicized and consolidated. We used OracleWarehouse Builder to extract, transform and load the source data into the Data Warehouse, by applyingthe KDD process. We have implemented the Data Warehouse as an Oracle OLAP. The knowledgeextraction has been performed using the Oracle Discoverer tool. This allowed users to take maximumadvantage of knowledge as a regular report or as ad hoc queries. We started by implementing the maintopic for this public institution, accounting for the movements of insured persons. The great success thathas followed the completion of this work has encouraged the NSSF to complete the achievement of othertopics of interest within the NSSF. We suggest in the near future to use Multidimensional Data Mining toextract hidden knowledge and that are not predictable by the OLAP.