The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
A Reference Model for Savings Bank
|
|
Author(s): Annett Mauser (IBM Business Consulting Services, Germany)
Copyright: 2007
Pages: 11
Source title:
Reference Modeling for Business Systems Analysis
Source Author(s)/Editor(s): Peter Fettke (Institute for Information Systems (IWi) at the German Research Center for Artificial Intelligence (DFKI), Saarbrücken, Germany)and Peter Loos (Institute for Information Systems (IWi) at the German Research Center for Artificial Intelligence (DFKI), Saarbrücken, Germany)
DOI: 10.4018/978-1-59904-054-7.ch010
Purchase
|
Abstract
With approximately 17490 well-defined modeling objects, the SKO -Datenmodell is probably the most extensive reference data model in German for the banking area. So far, this reference data model has been used in about 30 projects describing different subject areas. The detailed project data models that have been derived from these projects have been reintegrated into the generic reference data model, as far as the results are applicable to the entire Sparkassen-organisation. The SKO-Datenmodell was initially developed approximately 15 years ago. It is derived from the Financial Services Data Model (FSDM), which has been provided by IBM. The FSDM is a reference data model which is generally valid for the banking area. In contrast to the FSDM, the SKO-Datenmodell is specialized for the requirements of the Sparkassenorganisation. The basic elements of the reference data model are a conceptual design of data model abstraction levels, an extensive Methods and Procedures Handbook with precise quality requirements and an integrated tool support by m1 and Rochade . The different levels of the SKO-Datenmodell and the use of these levels in practice are described in this chapter.
Related Content
|
Yuvika Singh, Esha Bansal, Nisha Chanana.
© 2024.
26 pages.
|
|
Nitish Kumar Minz, Anshika Prakash, Meenal Arora, Rishi Chaudhary, Saurav Dixit.
© 2024.
14 pages.
|
|
Manoj Govindaraj, Chandramowleeswaran Gnanasekaran, R. Kandavel, Parvez Khan, Sinh Duc Hoang.
© 2024.
20 pages.
|
|
Ravishankar Krishnan, Elantheraiyan Perumal, Manoj Govindaraj, Logasakthi Kandasamy.
© 2024.
22 pages.
|
|
Sanjay Taneja, Rishi Prakash Shukla, Amandeep Singh.
© 2024.
11 pages.
|
|
Mune Moğol Sever.
© 2024.
23 pages.
|
|
Sujay Vikram Singh, Terrance Ancheary, Anish Mondal, Shashank Rajauria.
© 2024.
17 pages.
|
|
|