Data warehouses are efficient solutions for data-oriented decision support. Thus, in the last two decades they have widely spread in the international and Hungarian business environment – e.g. banking, telecommunications. As a next step, data warehouses also appeared in the public sector of the Western European countries and the USA.
In 2010, - with the sponsorship of the European Union - many projects started to implement data warehouse based information systems in the Hungarian higher education. These systems give the opportunity the Hungarian universities and colleges to satisfy their decision support demands and to fulfill governmental data supply duties with advanced IT tools.
The specialties of the higher education raise many questions – some highlighted ones as an example are the following: What impacts the specialties do have on the data warehouse projects? How can the success criteria of these projects be defined instead of analyzing the ROI indicators?
This thesis work introduces one of the most popular data warehouse systems: the SAP Business Warehouse (BW). The implementation of a BW data warehouse is in progress now on at least one Hungarian university. I have planned and implemented a data mart, which satisfies certain requirements of this university.
In the first part of the thesis work, I draw up the architecture of the SAP BW data warehouse system, the BW metamodel and data flow, the methods of the data acquisition, the BW-based data warehouse modeling and the business content. In the first chapter, I also introduce some tools for accessing data stored in the BW data warehouses.
In the second section of the thesis, I have described in detail the requirements of the client, and then I have presented the implementation plan of a business-financial data mart based on business content. Thereafter, I show the main steps of the implementation and the final product, with special focus on the relationship between the common data warehouse model and the implemented product.
As a conclusion, I have evaluated the implemented system, shared my personal experiences collected during the implementation and analysis, and provided an outlook on some additional possibilities of data warehousing in higher education.