The cube data model: a conceptual model and algebra for on-line analytical processing in data warehouses Export

@article{citeulike:2258683, abstract = {Data warehousing and On-Line Analytical Processing (OLAP) are two of the most significant new technologies in the business data processing arena. A data warehouse can be defined as a "very large" repository of historical data pertaining to an organization. OLAP refers to the technique of performing complex analysis over the information stored in a data warehouse. The complexity of queries required to support OLAP applications makes it difficult to implement using standard relational database technology. Moreover, there is currently no standard conceptual model for OLAP. There is clearly a need for such a model and an algebra as evidenced by the numerous SQL extensions offered by many vendors of OLAP products. In this paper, we address this issue by proposing a model of a data cube and an algebra to support OLAP operations on this cube. The model we present is simple and intuitive, and the algebra provides a means to concisely express complex OLAP queries.}, author = {Datta, Anindya and Thomas, Helen}, citeulike-article-id = {2258683}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/S0167-9236(99)00052-4}, citeulike-linkout-1 = {http://www.sciencedirect.com/science/article/B6V8S-3Y6H0VM-5/2/81f170c630890b0409b6dd9bb145a9e0}, doi = {10.1016/S0167-9236(99)00052-4}, journal = {Decision Support Systems}, keywords = {cube, data, database, datacube, informatics, olap, warehouse}, month = {December}, number = {3}, pages = {289--301}, posted-at = {2008-01-19 22:29:05}, priority = {0}, title = {The cube data model: a conceptual model and algebra for on-line analytical processing in data warehouses}, url = {http://dx.doi.org/10.1016/S0167-9236(99)00052-4}, volume = {27}, year = {1999} }

TY - JOUR ID - citeulike:2258683 L3 - citeulike-article-id:2258683 N2 - Data warehousing and On-Line Analytical Processing (OLAP) are two of the most significant new technologies in the business data processing arena. A data warehouse can be defined as a "very large" repository of historical data pertaining to an organization. OLAP refers to the technique of performing complex analysis over the information stored in a data warehouse. The complexity of queries required to support OLAP applications makes it difficult to implement using standard relational database technology. Moreover, there is currently no standard conceptual model for OLAP. There is clearly a need for such a model and an algebra as evidenced by the numerous SQL extensions offered by many vendors of OLAP products. In this paper, we address this issue by proposing a model of a data cube and an algebra to support OLAP operations on this cube. The model we present is simple and intuitive, and the algebra provides a means to concisely express complex OLAP queries. IS - 3 JF - Decision Support Systems EP - 301 TI - The cube data model: a conceptual model and algebra for on-line analytical processing in data warehouses VL - 27 SP - 289 KW - cube KW - data KW - database KW - datacube KW - informatics KW - olap KW - warehouse AU - Datta, Anindya AU - Thomas, Helen PY - 1999/12// UR - http://dx.doi.org/10.1016/S0167-9236(99)00052-4 ER -