Data which are collected in a DSS can not be analyzed directly from the data-collection questionnaires. Some data
processing needs to be done before the reasercher can do his analysis. The type of activities on the data varies from one
stage to another:
- during data entry, individuals have to be found or created, their data have to be modified, and their movements
have to be registered. This stage requires mainly activities, which are similar to online transactional data processing
(OLTP) in the business world. All these activities require access to the detailed data of the DSS.
during data management, the entered data have to be verified and corrected, and data have to be provided for
analysis. Data management requires detailed access to the DSS data, when data have to be corrected, but also
needs to look at aggregated data to have an overview of all entered data, in order to detect systematic errors.
Here a data manager is also doing online analytical processing (OLAP).
during data analysis, researchers are trying to find structures and dependencies in the data and an explanation for
these. A big part of data analysis is certainly the data mining part, where the researcher is ‘digging’ his way through
the data. This part requires heavy OLAP activities with constantly changing views on the data. The other part is the
analysis of a few core data, which are normally presented in a fixed format.