Efficient OLAP query processing across cuboids in distributed data warehousing environment

This research work introduces a novel approach to enhance the performance of distributed data warehouses. Distribution of data has been done across multiple data center for the underlying data warehouse to ensure parallel processing that improves the performance of the system. The proposed system focuses on data availability locally, resulting in faster query processing times. In order to further optimize the query processing and to alleviate the centralized data warehouse load, the study suggests distributing the cuboids at different sites to maintain the lattice of cuboids logically. Algorithms have been proposed to execute OLAP aggregation operations that significantly enhanced query response times in distributed data warehouse. Empirical tests on real-world datasets proved the method's effectiveness, showcasing its superiority in terms of reduced OLAP query execution time, enhanced space efficiency, minimized network transmission delays, reduced bandwidth requirements and more predictable and stable data transmission compared to existing approaches.