Data warehouse is typically a requirement for Business Intelligence purposes. A way to collect data from various source systems with the purpose of providing numbers, statistics and hopefully the answers to management questions. Management, questions and answers are all about the meaning of data, also called information.

Information is not about the data in source systems, but is about the meaning of data in the organization. Instead of technically try to align all source data, and map them into a single solution, a more efficient method of working exists. Fact Oriented Modeling allows the business side of the organization to explain what the information is they use, want and need. This business side of the data modeling allows the IT departments to map any source data towards that business model. No better way to capture and give meaning to data by a proper information model. The more business verbalisation a model can contain the more exact and meaningful the answers will be.

CaseTalk offers a unique way of capturing the conceptual information model which is not biased by already implemented source systems. By simply modelling the business perspective on their data and adding their verbalisations and examples, an unambiguous information model is realized. CaseTalk can export/transform these models for Data Warehouse support.

During all these model generations, verbalisations are maintained and the meaning is preserved all the way, from specifications till the final product. Mapping the source data systems towards this business information model should guarantee the proper handling of the data according to the business needs. Any product, aligned with this business model, will then remain stable in time, even when source systems change in the future. Source system changes then only require a mapping adjustment.

By having a business information model, one is able to verify which source data is available and which is not. This is a more efficient way of handling the information need, and provides a better insight in the organizations data.

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