Optimizing SQL queries in OLAP database systems

The augmenting data in the contemporary world triggers Data Warehouses (OLAP-Online Analytical Processing Systems) to maintain tremendous amount of data. Apart from being a data repository, data warehouses should also supply analytical and statistical data efficiently on demand. Data warehouses support unique features such as data mining, ad-hoc querying on data collected and integrated from many of the computerized systems used in organization. The issue of data extraction/updating is the most important factor for organizations to deploy real-time data warehouse solutions. This paper proposes several optimizing techniques for ensuring high performance data warehousing. The execution of this paper could serve as a tuning/bench-marking/management tool for overhauling data warehouse querying practices and processing. Experimental fall-outs of our implementation advocate that query performance and operational costs were significantly optimized.