Building data warehouse in Metropolia University of Applied Sciences
Abstract
Universities use many different data systems that store data in different databases. To get maximum benefit from this precious data it is necessary to build a data warehouse. In this building project data from different sources is integrated and processed to form that can be easily used in reporting and analyzing.
There are two different widespread data warehouse architectures: Inmon’s and Kimball’s. Metropolia started first with Inmon’s architecture. There were many problems and after many years we could not get much useful data to reporting. Later we changed to Kimball’s architecture and got good results with it.
There are two different widespread data warehouse architectures: Inmon’s and Kimball’s. Metropolia started first with Inmon’s architecture. There were many problems and after many years we could not get much useful data to reporting. Later we changed to Kimball’s architecture and got good results with it.
Keywords: |
Data warehouse; data mart; architecture; Inmon; Kimball
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References
Adamson, C. (2010). Star Schema, The Complete Reference. McGraw-Hill Osborne Media.
Kimball, R. (2002). The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
(Second Edition). Wiley.
Watson, H. J., Ariyachandra, T. (2005). Data Warehouse Architectures: Factors in the Selection
Decision and the Success of the Architectures. Retrieved May 2, 2013, from:
http://www.terry.uga.edu/~hwatson/DW_Architecture_Report.pdf.
DOI: 10.7250/eunis.2013.027
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EUNIS 2013
ISBN 978-9934-10-433-6 - online