DocumentCode :
2459087
Title :
The Credit Suisse Meta-data Warehouse
Author :
Jossen, Claudio ; Blunschi, Lukas ; Mori, Magdalini ; Kossmann, Donald ; Stockinger, Kurt
Author_Institution :
Credit Suisse AG, Zürich, Switzerland
fYear :
2012
fDate :
1-5 April 2012
Firstpage :
1382
Lastpage :
1393
Abstract :
This paper describes the meta-data warehouse of Credit Suisse that is productive since 2009. Like most other large organizations, Credit Suisse has a complex application landscape and several data warehouses in order to meet the information needs of its users. The problem addressed by the meta-data warehouse is to increase the agility and flexibility of the organization with regards to changes such as the development of a new business process, a new business analytics report, or the implementation of a new regulatory requirement. The meta-data warehouse supports these changes by providing services to search for information items in the data warehouses and to extract the lineage of information items. One difficulty in the design of such a meta-data warehouse is that there is no standard or well-known meta-data model that can be used to support such search services. Instead, the meta-data structures need to be flexible themselves and evolve with the changing IT landscape. This paper describes the current data structures and implementation of the Credit Suisse meta-data warehouse and shows how its services help to increase the flexibility of the whole organization. A series of example meta-data structures, use cases, and screenshots are given in order to illustrate the concepts used and the lessons learned based on feedback of real business and IT users within Credit Suisse.
Keywords :
data warehouses; feedback; information retrieval; meta data; organisational aspects; Credit Suisse; IT landscape; business analytics; business process; feedback; information item extraction; meta data structure; meta data warehouse; organization agility; organization flexibility; Data models; Data warehouses; Databases; Organizations; Resource description framework; Standards organizations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering (ICDE), 2012 IEEE 28th International Conference on
Conference_Location :
Washington, DC
ISSN :
1063-6382
Print_ISBN :
978-1-4673-0042-1
Type :
conf
DOI :
10.1109/ICDE.2012.41
Filename :
6228207
Link To Document :
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