Synonyms
Temporal data warehousing
Definition
A multi-dimensional Data Warehouse consists of three different levels: The schema level (dimensions, categories), the instance level (dimension members, master data) and the data level (data cells, transaction data). The process and methodology of performing changes on the schema and instance level to represent changes in the data warehouse’s application domain or requirements is called Data Warehouse Maintenance. Data Warehouse Evolution is a form of data warehouse maintenance where only the newest data warehouse state is available. Data Warehouse Versioning is a form of data warehouse maintenance where all past versions of the data warehouse are kept available. Dealing with changes on the data level, mostly insertion of new data, is not part of data warehouse maintenance, but part of a data warehouse’s normal operation.
Historical Background
Data warehouses are supposed to provide functionality for storing and analyzing data over a long...
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Multi-dimensional modeling with BW: ASAP for BW accelerator. Technical report, SAP Inc. 2000.
KALIDO dynamic information warehouse: a technical overview. Technical report, Kalido, 2004.
Bȩbel B, Eder J, Koncilia C, Morzy T, Wrembel R. Creation and management of versions in multiversion data warehouse. In: Proceedings of the 2004 ACM Symposium on Applied Computing; 2004. p. 717–23.
Blaschka M, Sapia C, Höfling G. On schema evolution in multidimensional databases. In: Proceedings of the 1st International Conference on Data Warehousing and Knowledge Discovery; 1999. p. 153–64.
Chamoni P, Stock S. Temporal structures in data warehousing. In: Proceedings of the 1st International Conference on Data Warehousing and Knowledge Discovery; 1999. p. 353–8.
Eder J, Koncilia C, Morzy T. The COMET metamodel for temporal data warehouses. In: Proceedings of the 14th International Conference on Advanced Information Systems Engineering; 2002. p. 83–99.
Eder J, Koncilia C, Wiggisser K. Maintaining temporal warehouse models. In: Proceedings of the International Conference on Research and Practical Issues of Enterprise Information Systems; 2006. p. 21–30.
Golfarelli M, Lechtenbörger J, Rizzi S, Vossen G. Schema versioning in data warehouses: enabling cross-version querying via schema augmentation. Data Knowl Eng. 2006;59(2):435–59.
Goller M, Berger S. Slowly changing measures. In: Proceedings of the ACM 16th International Workshop on Data Warehousing and OLAP; 2013. p. 47–54.
Jovanovic P, Romero O, Simitsis A, Abell A, Mayorova v. A requirement-driven approach to the design and evolution of data warehouses. Inf Syst. 2014;44(0):94–119.
Kimball R. Slowly changing dimensions. DBMS Mag. 1996;9(4):14.
Quix C. Repository support for data warehouse evolution. In: Proceedings of the 1st International Workshop on Design and Management of Data Warehouses; 1999.
Ravat F, Teste O. A temporal object-oriented data warehouse model. In: Proceedings of the 11th International Conference on Database and Expert Systems Applications; 2000. p. 583–92.
Rundensteiner EA, Koeller A, Zhang X. Maintaining data warehouses over changing information sources. Commun ACM. 2000;43(6):57–62.
Sarda NL. Temporal issues in data warehouse systems. In: Proceedings of the International Symposium on Database Applications in Non-Traditional Environments; 1999.
Vaisman A, Mendelzon A. A temporal query language for OLAP: implementation and a case study. In: Proceedings of the 8th International Workshop on Database Programming Languages; 2001. p. 78–96.
Yang J, Widom J. Maintaining temporal views over non-temporal information sources for data warehousing. In: Advances in Database Technology, Proceedings of the 6th International Conference on Extending Database Technology; 1998. p. 389–403.
Zhuge Y, Garcia-Molina H, Hammer J, Widom J. View maintenance in a warehousing environment. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 1995. p. 316–27.
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Eder, J., Koncilia, C., Wiggisser, K. (2018). Data Warehouse Maintenance, Evolution, and Versioning. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_118
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