An analytical model for data persistence in Business Data Warehouses

Redundancy of data persistence in Data Warehouses is mostly justified with better performance when accessing data for analysis. However, there are other reasons to store data redundantly, which are often not recognized when designing data warehouses. Especially in Business Data Warehouses, data management via multiple persistence levels is necessary to condition the huge amount of data into an adequate format for its final usage. Redundant data allocates additional disk space and requires time-consuming processing and huge effort for complex maintenance. That means in reverse: avoiding data persistence leads to less effort. The question arises: What data for what purposes do really need to be stored? In this paper, we discuss decision support and evaluation approaches beyond cost-based comparisons. We use a compendium of purposes for data persistence. We define a model that includes objective indicators and subjective user preferences for decision making on data persistence in Business Data Warehouses. We develop an indicator system that enables the measurement of technical as well as business-related facts. With multi-criteria decision methodology, we present a framework to objectively compare different alternatives for data persistence. Finally, we apply our developed method to a real world Business Data Warehouse and show applicability and integration of our model in an existing system.