Methodological guidelines for reducing the complexity of data warehouse development for transactional blood bank systems

Over time, data warehouse (DW) systems have become more difficult to develop because of the growing heterogeneity of data sources. Despite advances in research and technology, DW projects are still too slow for pragmatic results to be generated. Here, we address the following question: how can the complexity of DW development for integration of heterogeneous transactional information systems be reduced? To answer this, we proposed methodological guidelines based on cycles of conceptual modeling and data analysis, to drive construction of a modular DW system. These guidelines were applied to the blood donation domain, successfully reducing the complexity of DW development.

► Appliance of some good practices to facilitate data warehouse system development
► Modularizing a data warehouse system makes its maintenance easier.
► A conceptual model guides data warehouse system construction
► Data analyses are important for data warehouse system debugging.
► Combined use of specific practices promotes agile data warehouse development.