Credit Suisse
Business Data Modeling

Large enterprises have complex business processes

Enterprise-wide data models are pre-requisites for successful data warehousing. Most enterprise data models have a lot in common, e.g. base entities for customers, services, accounting, etc. - quite independently of the specific area of their businesses. Domain differences, however, become soon apparent when drilling down a level deeper. Telecom, pharmaceutical, retail or insurance companies offer different products which must be reflected in their respective business data model. Leading database software manufacurers produce generic, domain specific enterprise-wide data models in order to support the tedious and often controversial task of creating a data warehouse.

Even "industry standard" data models are vastly different in terms of their abstraction level. More generic models, e.g. those of Oracle, are often easier to adapt to new business requirements. On the other hand, specific data models, e.g. those of Teradata, might be easier understood by end-users, like reporting specialists. Due to the complexity of the business processes such data models can incorporate several thousands entities. The trade-off between generic and specific models are best measured by implementations: load and query performance, data quality, TCO, etc.

Our contribution

Data modeling has been in our focus for a long time. Some of our stories:

  • International wholesale and retail enterprise with over 100,000 articles, food and non-food, several hundreds of wholesale stores in most of Europe and parts of Asia. Data modeling of sales operations on the item level to be integrated into the enterprise data warehouse.
  • International expert know-how services company in the insurance business with sales offices in about 60 counties globally. Data modeling of the core knowledge base to be maintained in a redesigned distributed application.
  • Mobile telecom company operating in Europe and Asia. Customization of the Oracle Communication Data Model in a data warehouse re-engineering project.
  • International bank (1) based in Switzerland. Data modeling of the Client Analytics data mart as an annex to the inhouse Business System Data Warehouse.
  • Commodity trading company in the energy industry based in Switzerland. Data modeling of the securities and futures trading data mart. Our solution to modeling inter-related dimensions through factor decomposition is of particular interest.
  • International bank (2) based in Switzerland. Data modeling of the Investment Products and Services data mart.
  • Start-up company in the social networking development for enterprises. Portal development in the Liferay framework. Data modeling of enterprise-related extensions of the core data model.