Abstract

Data in demographic surveillance systems (DSS) are normally stored in database systems, which were designed according to the principles of relational data models. These are optimized to store detailed information on individuals efficiently and without contradictions, but require a good understanding of the abstract data model for data-extraction.

As a result, data analysis of DSS tends to be challenging for the researcher who wants to use demographic data in his research. Data are difficult to get directly from the database system, while on the other hand pre-processed results are often not specific enough to suit the researchers' demands.

Data storage in info-cubes forms a good compromise between flexibility and simplicity of data analysis. Info cubes form the heart pieces of data warehouses, which are the data architecture in modern management information systems. These are a supplementary platform to operational data storage and are specifically optimized to facilitate data analysis.

Primary aim of info-cubes is no longer absence of redundancy, as in relational data models, but optimization of analytical processes. Info-cubes aggregate data in semantic units according to possible analysis topics. Detailed information as needed by operational processes is eliminated as much as possible.