The Credit Suisse Meta-data Warehouse

Claudio Jossen, Lukas Blunschi, M. Mori, Donald Kossmann, Kurt Stockinger
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引用次数: 6

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.
瑞士信贷元数据仓库
本文描述了瑞士信贷自2009年以来的元数据仓库。与大多数其他大型组织一样,瑞士信贷拥有复杂的应用程序环境和几个数据仓库,以满足其用户的信息需求。元数据仓库解决的问题是提高组织在诸如开发新的业务流程、新的业务分析报告或实现新的监管需求等变化方面的敏捷性和灵活性。元数据仓库通过提供在数据仓库中搜索信息项和提取信息项沿袭的服务来支持这些更改。设计这种元数据仓库的一个困难是,没有标准的或众所周知的元数据模型可用于支持此类搜索服务。相反,元数据结构本身需要灵活,并随着IT环境的变化而发展。本文描述了Credit Suisse元数据仓库的当前数据结构和实现,并展示了其服务如何帮助提高整个组织的灵活性。本文给出了一系列元数据结构、用例和屏幕截图示例,以便根据瑞士信贷内部实际业务和IT用户的反馈说明所使用的概念和经验教训。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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