Title: Data warehouse design on the basis of Hierarchical Degenerate Snowflake (HDS)

Authors: Morteza Zaker, Norizan Binti Mohd. Yasin, Somnuk Phon-Amnuaisuk, Su-Cheng Haw

Addresses: Faculty of Computer Science and Information Technology Building, Department of Information Science, University of Malaya, 50603 Kuala Lumpur, Malaysia. ' Faculty of Computer Science and Information Technology Building, Department of Information Science, University of Malaya, 50603 Kuala Lumpur, Malaysia. ' Faculty of Information Technology, Multimedia University, Persiaran Multimedia, 63100 Cyberjaya, Selangor, Malaysia. ' Faculty of Information Technology, Multimedia University, Persiaran Multimedia, 63100 Cyberjaya, Selangor, Malaysia

Abstract: Two of the most data model in Data Warehouse (DW) and advanced database includes star and snowflake schema, which play pivotal roles in the underlying performance. Today, DW queries comprise a group of aggregations and joining operations. As a result, snowflake schema does not seem to be an adequate option since several relations must combine to provide answers for queries that involve aggregation. In spite of its widespread application and undeniable advantages, snowflaking technique has certain theoretical and practical demerits. This paper proposes Hierarchical Degenerate Snowflake (HDS) as an alternative logical data model to achieve DW structure to improve the query performance.

Keywords: data warehouse design; OLAP; logical data modelling; query processing; data warehousing; hierarchical degenerate snowflake; snowflaking.

DOI: 10.1504/IJBIDM.2011.039410

International Journal of Business Intelligence and Data Mining, 2011 Vol.6 No.2, pp.154 - 183

Published online: 22 Apr 2015 *

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