Domain/Mapping Model: A Novel Data Warehouse Data Mode
Keywords:
data warehouse, data models, relational/normalized model, data vault model, anchor model, dimensional model, domain/mapping modelAbstract
In order for a data warehouse to be able to adequately fulfill its integrative and historical purpose, its data model must enable the appropriate and consistent representation of the different states of a system. In effect, a DW data model, representing the physical structure of the DW, must be general enough, to be able to consume data from heterogeneous data sources and reconcile the semantic differences of the data source models, and, at the same time, be resilient to the constant changes in the structure of the data sources. One of the main problems related to DW development is the absence of a standardized DW data model. In this paper a comparative analysis of the four most prominent DW data models (namely the relational/normalized model, data vault model, anchor model and dimensional model) will be given. On the basis of the results of [1]a, the new DW data model (the Domain/Mapping model- DMM) which would more adequately fulfill the posed requirements is presented.References
I. Bojicic, Z. Marjanovic, N. Turajlic, M. Petrovic, M. Vuckovic and V. Jovanovic (2016), A comparative analysis of data warehouse data models, Computers Communications and Control (ICCCC), 2016 6th International Conference on, IEEE Xplore, e-ISBN 978-1-5090- 1735-5, doi: 10.1109/ICCCC.2016.7496754, 151-159. https://doi.org/10.1109/ICCCC.2016.7496754
W. Inmon, Building the Data Warehouse. Wiley, 2002.
R. Kimball, L. Reeves, M. Ross and W. Thornthwaite (1998), The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing, and Deploying Data Warehouses, Wiley, 1998.
Object Management Group (2002); Common Warehouse Metamodel, available at: http://www.omg.org/cgi-bin/doc?formal/03-03-02.pdf
O. Regardt, L. Ronnback, M. Bergholtz, P. Johannesson and P. Wohed (2009); Anchor Modeling: An Agile Modeling Technique Using the Sixth Normal Form for Structurally and Temporally Evolving Data, in Proc. of ER09 (Brazil) , LNCS, 5829(1): 234-250. https://doi.org/10.1007/978-3-642-04840-1_19
D. Linstedt (2010); Data Vault Modeling Specification v1.0.9., available at: http:// danlinstedt.com/datavaultcat/standards/dv-modeling-specification-v1-0-8/
B. Lazarevic, Z. Marjanovic, N. Anicic and S. Babarogic (2010). Baze podataka. Fakultet organizacionih nauka, 2010 (Textbook in Serbian).
E. F. Codd (1969); Derivability, Redundancy and Consistency of Relations Stored in Large Data Banks, IBM Research Report, San Jose, California, 1969.
E. F. Codd (1970); A Relational Model of Data for Large Shared Data Banks, in Communications of the ACM, 13(6):377-387. https://doi.org/10.1145/362384.362685
D. Linstedt (2002); Data Vault Series 1 - Data Vault Overview, available at: http://www. tdan.com/view-articles/5054/
D. Linstedt (2011); Super Charge Your Data Warehouse: Invaluable Data Modeling Rules to Implement Your Data Vault, CreateSpace Independent Publishing Platform, 2011.
D. Linstedt (2003); Data Vault Series 2 - Data Vault Components, available at: http://www.tdan.com/view-articles/5155/
L. Ronnback, O. Regardt, M. Bergholtz, P. Johannesson, P. Wohed (2010); Anchor modeling - Agile information modeling in evolving data environments, in Data & Knowledge Engineering, 69(12):1229-1253.
R. Kimball and M. Ross (2013);
The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, Wiley, 3rd ed., 2013.
M. Golfarelli and S. Rizzi (2009);
Data Warehouse Design - Modern Principles and Methodologies, McGraw - Hill, 2009.
Anchor Modeling Tool, available at: http://www.anchormodeling.com/modeler
E. Malinowski and E. Zimanyi (2008); Advanced Data Warehouse Design - From Conventional to Spatial and Temporal Applications, Springer-Verlag Berlin Heidelberg, 2008.
R. T. Snodgrass, I. Ahn (1986); Temporal Databases, in IEEE Computer, 19(9):35 - 42.
C. Jensen, J. Clifford, R. Elmasri, S. K. Gadia, P. J. Hayes, S. Jajodia (1994);
A Consensus Glossary of Temporal Database Concepts, SIGMOD Record, 23(1):52 - 64. https://doi.org/10.1145/181550.181560
H. Gregersen, J.S. Jensen (1999);
Temporal Entity-Relationship models a survey, IEEE Transactions on Knowledge and Data Engineering, 11: 464-497. https://doi.org/10.1109/69.774104
L. Ronnback, O. Regardt, M. Bergholtz, P. Johannesson, P. Wohed 92010); From Anchor Model to Relational Database, available at: http://www.anchormodeling.com/wp-content/ uploads/2010/09/AM-RDB.pdf
M. Golfarelli, J. Lechtenborger, S. Rizzi, G. Vossen (2006); Schema versioning in data warehouses: Enabling cross-version querying via schema augmentation, in Data & Knowledge Engineering, 59(2):435-459.
B. Inmon (2004); The Single Version of The Truth, Business Intelligence Network (Powell Media LLC), available at: http://www.b-eye-network.com/view/282.
R. Damhof (2008); The next generation EDW, available at: http://prudenza.typepad. com/files/
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