A Hybrid Data Warehouse Model to Improve Mining Algorithms


The performance of different Data Mining Algorithms including Classification, Clustering, Association, Prediction and others are highly related to the approaches used in Data Warehouse design and to the way the data is stored (lightly summarized, highly summarized and detailed).Detailed data is important to get detailed reports but as the amount of data is huge this represents a big challenge to the mining algorithms, on the other hand, the summarized data leads to better algorithms performance but the lack of the required knowledge may affect the overall mining process.Knowledge extraction and mining algorithms performance and complexities represent a big challenge in data analysis field, hence the work in this paper represents a proposed approach to improve the algorithms performance throughout well designed warehouse and data reduction technique.