ABSTRACT
OLAP tools divide concepts based on whether they are used as analysis dimensions, or are the fact subject of analysis, which gives rise to star shape schemas. Operations are always provided to navigate inside such star schemas. However, the navigation among different stars is usually overlooked. This paper studies different kinds of Object-Oriented conceptual relationships (part of UML standard) between stars (namely Derivation, Generalization, Association, and Flow) that allow to drill across them.
- A. Abelló, J. Samos, and F. Saltor. Understanding Facts in a Multidimensional Object-Oriented Model. In Proc. of the 4th Int. Workshop on Data Warehousing and OLAP(DOLAP), pages 32--39. ACM Press, 2001.]] Google ScholarDigital Library
- A. Abelló, J. Samos, and F. Saltor. YAM2 (Yet Another Multidimensional Model): An extension of UML. In Proc. of the Int. Database Engineering & Applications Symposium (IDEAS'02), pages 172--181. IEEE Press, 2002.]] Google ScholarDigital Library
- L. Cabibbo and R. Torlone. A logical approach to multidimensional databases. In Advances in Database Technology - EDBT'98}, number 1377 in LNCS, pages 183--197. Springer, 1998.]] Google Scholar
- J. Eder and C. Koncilia. Changes of Dimension Data in Temporal Data Warehouses. In Proc. of the 3rd Int. Conf. on Data Warehousing and Knowledge Discovery (DaWaK), volume 2114 of LNCS. Springer, 2001.]] Google ScholarDigital Library
- W. Giovinazzo. O-O Data Warehouse Design. Prentice Hall, 2000.]]Google Scholar
- M. Golfarelli, D. Maio, and S. Rizzi. The Dimensional Fact Model: a Conceptual Model for Data Warehouses. Int. Journal of Cooperative Information Systems, 7(2&3):215--247, 1998.]]Google ScholarCross Ref
- V. Gopalkrishnan, Q. Li, and K. Karlapalem. Star/snow-flake schema driven object-relational data warehouse design and query processing strategies. In Proc. of 1st Int. Workshop on Data Warehousing and Knowledge Discovery (DaWaK), number 1676 in LNCS, pages 11--22. Springer, 1999.]] Google ScholarDigital Library
- W. H. Inmon. Building the Data Warehouse. John Wiley & Sons, 1996.]] Google ScholarDigital Library
- ISO. ISO/IEC 9075:1999: Information technology --- Database languages --- SQL. Int. Organization for Standardization, 1999.]]Google Scholar
- R. Kimball. The Data Warehouse toolkit. John Wiley & Sons, 1996.]]Google ScholarDigital Library
- R. Kimball, L. Reeves, M. Ross, and W. Thornthwaite. The Data Warehouse lifecycle toolkit. John Willey & Sons, 1998.]] Google ScholarDigital Library
- W. Lehner. Modeling large scale OLAP scenarios. In Advances in Database Technology - EDBT'98, number 1377 in LNCS. Springer, 1998.]] Google ScholarDigital Library
- D. L. Moody and M. A. R. Kortink. From enterprise models to dimensional models: A methodology for data warehouse and data mart design. In Proc. of 2nd Int. Workshop on Design and Management of Data Warehouses (DMDW). Swiss Life, 2000.]]Google Scholar
- OMG. Unified Modeling Language Specification, September 2001. Version 1.4.]]Google Scholar
- T. B. Pedersen. Aspects of Data Modeling and Query Processing for Complex Multidimensional Data. PhD thesis, Faculty of Engineering and Science, Aalborg University (Denmark), 2000.]]Google Scholar
- T. B. Pedersen and C. S. Jensen. Multidimensional data modeling for complex data. In Proc. of 15th Int. Conf. on Data Engineering (ICDE), pages 336--345. IEEE Computer Society, 1999.]] Google ScholarDigital Library
- C. Sapia, M. Blaschka, G. Höfling, and B. Dinter. Extending the E/R model for the multidimensional paradigm. In Proc. Int. Workshop on Data Warehouse and Data Mining (DWDM) in conjunction with the ER'98, number 1552 in LNCS, pages 105--116. Springer, 1999.]] Google Scholar
- A. Shoshani and M. Rafanelli. A Model for Representing Statistical Objects. In Proc. of the 3rd Int. Conf. on Information Systems and Management of Data (COMAD). McGraw-Hill, 1991.]]Google Scholar
- J. C. Trujillo, M. Palomar, J. Gmez, and I.-Y. Song. Designing Data Warehouses with OO Conceptual Models. IEEE Computer, 34(12):66--75, 2001.]] Google ScholarDigital Library
- N. Tryfona, F. Busborg, and J. G. B. Christiansen. starER: A conceptual model for data warehouse design. In Proc. of ACM 2nd Int. Workshop on Data Warehousing and OLAP (DOLAP), 1999.]] Google ScholarDigital Library
Index Terms
- On relationships offering new drill-across possibilities
Recommendations
Implementing operations to navigate semantic star schemas
DOLAP '03: Proceedings of the 6th ACM international workshop on Data warehousing and OLAPIn the last years, lots of work have been devoted to multidimensional modeling, star shape schemas and OLAP operations. However, "drill-across" has not captured as much attention as other operations. This operation allows to change the subject of ...
Automatic validation of requirements to support multidimensional design
It is widely accepted that the conceptual schema of a data warehouse must be structured according to the multidimensional model. Moreover, it has been suggested that the ideal scenario for deriving the multidimensional conceptual schema of the data ...
Efficient processing of drill-across queries over geographic data warehouses
DaWaK'11: Proceedings of the 13th international conference on Data warehousing and knowledge discoveryDrill-across SOLAP queries (spatial OLAP queries) allow for strategic decision-making through the use of numeric measures from distinct fact tables that share dimensions and by the evaluation of spatial predicates. Despite the importance of these ...
Comments