Client: Chain of super markets in India. Scenario: The operations involve the generation of raw data from the OLTP systems throughout the country. This raw data is generated via various means, including, C, SQLPLUS, Dbase, and other proprietary software systems. This data is transferred to the main HQ systems where it undergoes the operations of ELT (Extraction, loading & Transformation). The Entire operation is implemented via SQL*Loader, and various PL/SQL codes written by our DBAs. There is a load of 2GB + data everyday. At the end of three month periods the data is summarized and stored as summary tables, and the non-summarized data is purged from the database. Micro Strategy is used as the BI tool for generating the various reports required for the Management. Our Solutions: 1. Ensuring that the data which has been obtained from the multiple OLTP sources from across the country is correct and consistent. 2. The formats in which the data is obtained from the sources are not always in the format of the Staging or Data Warehousing (DW)area. We had to generate scripts to get the data into the required format. Based upon the type of the data, it was either loaded using SQL*Loader or the External Tables. We also used the new feature of constraints Exceptions into Exceptions to ensure that no duplicate records found their way inside the Data Warehousing schema. 3. Multiple features like Merge, PL/SQL coding were used to transfer the data from the staging area to the DW area. 4. The data is retained in the DW schema only for a duration of three e Months. At the end of this period the data is summarized and kept in side the summary schema. It is furthermore purged from the DW schema too. For all these steps we also had to provide scripts to further ensure that whatever data is received in one stage is moved on to the next stage. 5. Even though we did not specialize in the Business Intelligence (BI) Micro Strategy Tool, our DBAs checked up the tool, and learnt it while doing the various performance checks, and were able to specify changes not only in the database but also for the BI. These changes allowed the BI tool to work more efficiently. A number of Matrices were modified to allow for better Performance beneficent code.